Nicolae Lucian Mihet

• Ganesan, Manikandan; Chokkalingam, Bharatiraja; Mihet, Nicolae Lucian; Verma, Rajesh & Mihet, Nicolae Lucian (2026). A Hierarchical Real-Time Object Detection and Fine-Grained Classification framework for Autonomous Driving. IEEE Access. doi: 10.1109/ACCESS.2026.3711217. Fulltekst i vitenarkiv
• Ramya, K.; Gopalakrishnan, Janaki; Verma, Rajesh; Chokkalingam, Bharatiraja & Mihet, Nicolae Lucian (2026). Experimental investigation of a π–L EMI filter for conducted noise suppression in a dual active bridge converter. Results in Engineering (RINENG). 32. doi: 10.1016/j.rineng.2026.111795. Fulltekst i vitenarkiv
• Ramya, K.; i Gopalakrishnan, Janaki; Verma, Rajesh; a Chokkalingam, Bharatiraja & Mihet-Popa, Lucian (2026). RedirectingExperimental investigation of a π–L EMI filter for conducted noise suppression in a dual active bridge converter. Results in Engineering (RINENG). Fulltekst i vitenarkiv Vis sammendrag

  High-frequency dual active bridge (DAB) converters used in electric vehicle (EV) charging and bidirectional energy conversion systems often generate severe conducted electromagnetic interference (EMI), including common-mode (CM) and differential-mode (DM) noise, which complicates compliance with automotive EMI standards. This paper proposes an impedance-based EMI filter design methodology for a high-frequency voltage-mode controlled DAB converter. A passive π–L filter topology is analytically designed to simultaneously suppress CM and DM noise while considering converter–filter interaction and stability constraints. Unlike conventional trial-and-error approaches, the proposed method enables predictable broadband attenuation through impedance-oriented analysis. A 500 W hardware prototype operating between a 60 V source and a 48 V battery is developed to validate the proposed approach under single-phase-shift control, achieving a peak efficiency of 97.6%. Conducted emissions are evaluated using a line impedance stabilization network (LISN) in accordance with CISPR 25 Class 5 standards over the frequency range of 150 kHz–30 MHz. Experimental results show that the optimized filter achieves full EMI compliance with significant attenuation margins, while maintaining high conversion efficiency. The close agreement between analytical and experimental results demonstrates the effectiveness and practical applicability of the proposed EMI-aware DAB design methodology for high-density Grid-to-Battery and Battery-to-Grid systems.

• Deepak, M.; Chokkalingam, Bharatiraja; Verma, Rajesh; Sathiyasekar, K. & Mihet, Nicolae Lucian (2026). Sensorless Model Predictive Direct Torque Regulation with Modified Switching Table for Double‑Pole Salient Machines to Improve the Performance. IEEE Access. doi: 10.1109/ACCESS.2026.3675882. Fulltekst i vitenarkiv
• Sadagopan, A.; Udhayakumar, K.; Verma, Rajesh; Chokkalingam, Bharatiraja & Mihet, Nicolae Lucian (2026). Predictive Control Techniques for Switched Reluctance Motor: An Overview. IEEE Access. Fulltekst i vitenarkiv Vis sammendrag

  The Switched Reluctance Motor (SRM) is a developing electric drive innovation that outperforms the Induction Motor (IM) and the Permanent Magnet Synchronous Motor (PMSM) in numerous industrial uses, including Electric Vehicles, HVAC Systems, and applications that demand high speeds and reliable fault tolerance. Nonetheless, it has many drawbacks, such as Torque Ripple, Acoustic Noise, and Non-Linear Torque Characteristics, which may restrict its use in certain industrial settings. This article gives an overview of Predictive Control (PC) techniques for controlling current-torque and Torque-Speed characteristics, thereby eliminating main issues such as torque ripple and current ripple, and compensating for Nonlinear Torque characteristics. The paper analyzes Model-based Predictive Control (MPC) techniques and Model-free Predictive Control techniques from a modeling perspective, including switching vector optimization methods, cost function choices, and control efficiency. Finally, the existing difficulties and future advancements in implementing MPC schemes in SRM are discussed.

• Manimaran, S; Chokkalingam, Bharatiraja; Verma, Rajesh; Datta, Shubhabrata & Mihet-Popa, Lucian (2026). Design and Development of Multi-Utility Electric Vehicle Powertrain System. IEEE Access. 14, s. 28701–28716. doi: 10.1109/access.2026.3657296. Fulltekst i vitenarkiv
• Islam, Fayzul; Ahmed, Ibrahim Abbas Elamen & Mihet, Nicolae Lucian (2025). Demand-Side Management in Residential Buildings: Load Shifting and Cost Savings via a Cloud-Based IoT-BEMS. I 2025, IECON (Red.), IECON 2025 – 51st Annual Conference of the IEEE Industrial Electronics Society. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798331596811. s. 1–7. doi: 10.1109/IECON58223.2025.11221160. Fulltekst i vitenarkiv
• Mahesh, Aganti; Chokkalingam, Bharatiraja; Verma, Rajesh & Mihet-Popa, Lucian (2025). 7.7 kW Inductive Coupling Three-Phase Coil Wireless Power Transfer Pads for Electric Vehicles Charging. IEEE Access. 13, s. 54648–54662. doi: 10.1109/ACCESS.2025.3552825. Fulltekst i vitenarkiv Vis sammendrag

  Modern electric vehicle (EV) wireless charging systems (WCSs) rely heavily on Resonant Inductive Power Transfer (RIPT), which offers a flawless integration of safety, dependability, and automated functionality. In RIPT-based WCS, the design of magnetic pads is a critical factor that significantly influences power transfer efficiency. This component is essential for optimizing the system’s performance. Three-phase couplers (TPCs) surpass single-phase designs by offering higher energy transfer capacity, along with benefits such as rotating magnetic flux and lessened use of ferrite materials. This article provides an in-depth analysis of a TPC with a circular design, referred to as the “Three Half Circular Coil” (3HCC) pad. Three half-circular coils are positioned in a circle to form the 3HCC pad, delivering advantages such as improved angular misalignment tolerance, optimized ferrite utilization, and simplified construction. The effectiveness of the 3HCC design is evaluated using Matlab and FEA tools for a 7.7 kW WCS, with comparisons made against tripolar, three-phase rectangular, and traditional single-phase circular coil designs. To validate the 3HCC design, a 7.7 kW lab prototype was developed, focusing on coupling and cross-coupling effects influenced by various coil attributes like misalignment, coil position, and the number of turns. The research emphasizes the vital role of RIPT in EV charging and demonstrates the superiority of TPCs compared to their single-phase equivalents. Furthermore, it demonstrates the proposed 3HCC design’s effectiveness in improving charging efficiency.

• Islam, Fayzul; Ahmed, Ibrahim Abbas Elamen & Mihet-Popa, Lucian (2025). Development and testing of an IoT platform with smart algorithms for building energy management systems. Energy and Buildings. ISSN 0378-7788. 344. doi: 10.1016/j.enbuild.2025.115970. Fulltekst i vitenarkiv Vis sammendrag

  Buildings are a major cause of carbon emissions. The building sector is responsible for around 40% of energy consumption and for about 30% of CO2 emissions. Building Energy Management Systems (BEMS) are crucial for enhancing energy efficiency, and energy flexibility, and mitigating the environmental impact of buildings, which account for a significant amount of global energy use and greenhouse gas emissions. This study addresses the limitations of traditional BEMS by proposing a cloud-based IoT-BEMS with an intuitive user interface and advanced machine learning algorithms for energy optimization. The system integrates demand-side management techniques, including two main principles, load shifting through demand response and energy efficiency, allowing users to control appliances without requiring technical expertise. The results demonstrate significant energy savings, particularly in water heater optimization, with an average reduction of 24.23% in energy consumption. Additionally, the Proximal Policy Optimization (PPO) algorithm used for electric vehicle (EV) charging resulted in an average cost saving of 30.6% by leveraging off-peak electricity rates. The platform’s real-time data processing and user-friendly interface make it a robust solution for residential energy management, effectively balancing energy savings with user comfort. This research underscores the potential of IoT and machine learning in revolutionizing building energy management, contributing to the Sustainable Development Goals.

• Mahesh, Aganti; Chokkalingam, Bharatiraja; Verma, Rajesh & Mihet-Popa, Lucian (2025). Load Invariant CC and CV Modes for Static/Dynamic Wireless Charging System with Half-Bridge Multi-Leg Converter Topology. IEEE Access. 13, s. 9654–9665. doi: 10.1109/ACCESS.2025.3526654. Fulltekst i vitenarkiv Vis sammendrag

  Resonant Inductive Power Transmission (RIPT) is an advanced Wireless Power Transfer (WPT) technology, emerging as a secure and efficient solution for Electric Vehicle (EV) charging. Although Dynamic Wireless Charging Systems (DWCS) reduce the need for large batteries compared to static charging, they require higher initial investments. This study introduces a novel approach utilizing LCC-S compensation to achieve load-invariant Constant Current (CC) and Constant Voltage (CV) outputs at two distinct Zero Phase Angle (ZPA) frequencies in DWCS, leveraging a half-bridge-based multi-legged inverter configuration. The article presents a new method with fewer iterations to determine the optimal compensation parameters, ensuring that both the CC and CV outputs with ZPA comply with the SAE J2954 frequencies standards. The half-bridge-based DWCS with LCC-S compensation is designed to operate in either CC or CV mode, depending on whether the application involves static or dynamic charging. A 1-kW LCC-S compensated DWCS prototype was developed and built to verify and support the theoretical findings and analysis. This study offers valuable insights for optimizing RIPT technology, making EV charging more efficient and cost-effective.

• Deepak, Mohanraj; Umavathi, M.; Chokkalingam, Bharatiraja; Verma, Rajesh & Mihet-Popa, Lucian (2025). Enhancing Performance Towards Torque and Flux Control through a Hybrid Approach of Intelligent and DTC for SRM Drives. IEEE Access. 13, s. 92168–92179. doi: 10.1109/ACCESS.2025.3569277. Fulltekst i vitenarkiv Vis sammendrag

  Switched Reluctance Motors (SRMs) are considered the preferred choice for next-generation electric vehicle (EV) traction motor applications due to their simple rotor structure and favorable power and torque characteristics. However, SRM drives suffer from high torque ripples, which can cause severe vibrations and acoustic noise. Moreover, the highly nonlinear characteristics of SRMs complicate their control and modeling, making it a significant challenge to achieve optimal performance. Therefore, this paper proposes a Direct Torque Control (DTC) strategy for SRMs, which incorporates a modified dynamic precise model and an Adaptive Neuro-Fuzzy Inference System (ANFIS). First, a DTC technique based on a two-level hysteresis controller with an appropriate switching scheme is introduced for instantaneous torque control, ensuring proper torque tracking with a smooth torque profile. Second, a novel hybrid intelligent ANFIS model is developed for accurate flux and torque estimation and optimal selection of switching angles. The proposed method employs a multi-objective function to fully exploit the torque production capability of the SRM, minimize torque ripple, and enhance operational efficiency. The proposed solutions are compared with conventional DTC schemes, and experimental evaluations demonstrate significant reductions in torque ripple, flux ripple, and current distortion.

• MADHAVAN, MEENAKSHI; NALLAPERUMAL, CHELLAMMAL; Verma, Rajesh; Chokkalingam, Bharatiraja & Mihet-Popa, Lucian (2025). A Study on the Performance Evaluation of F-Type Multilevel Inverters Employing Phase Disposition Carrier PWM Schemes. IEEE Access. 13, s. 48286–48305. doi: 10.1109/ACCESS.2025.3549589. Fulltekst i vitenarkiv Vis sammendrag

  This research presents a three-phase, three-level F-type inverter utilizing a four switch per leg and a DC link. The proposed structure necessitates less power components than traditional three-level inverter topologies, hence reducing switching stress and loss as thereby decreasing the topology cost. The suggested inverter employs a carrier-based pulse width modulation (PWM) technique, including Sine PWM, Sixty-Degree PWM, and Switching Frequency Optimal (SFO) PWM, to achieve the necessary output voltage. The inverter operates with various amplitude and frequency modulation indices (ma, mf), and its performance is evaluated based on total harmonic distortion (THD), fundamental output voltage, inverter losses, and efficiency. To demonstrate the efficacy of the proposed configuration, a 400 W prototype of the inverter is developed, and empirical findings are provided. The suggested inverter demonstrates exceptional performance with a modulation index of ma =0.9 and mf =100 under SFO PWM, enabling improved THD performance, increased output voltage, and greater efficiency. As the switching frequency increases, a greater portion of the harmonic spectrum shifts away from the fundamental frequency, so assuring that the SFO PWM technique requires reduced filter size.

• Ganesan, Manikandan; Chokkalingam, Bharatiraja; Mihet, Nicolae Lucian; Verma, Rajesh & Mihet, Nicolae Lucian (2025). Bridging the Sim-to-Real Gap in Motion Planning for Autonomous Electric Vehicles Using Autoware: A Comparative Study of Simulation and Real-World Deployment. IEEE Access. 13, s. 136210–136225. doi: 10.1109/ACCESS.2025.3587991. Fulltekst i vitenarkiv Vis sammendrag

  Road traffic accidents result in over 1.35 million fatalities annually, highlighting the urgent need for safer transportation systems. Autonomous Electric Vehicles (AEVs), powered by advancements in Intelligent Transportation Systems (ITS), offer a promising solution by enhancing road safety and efficiency. This study focuses on trajectory planning for AEVs, a critical component for safe navigation in dynamic environments. Using Autoware.ai, an open-source modular platform, a novel interface integrating custom point cloud (PCD) and vector maps for precise localization and navigation was developed. The proposed method was tested in both simulation and real-world scenarios on the SRM IST campus, addressing challenges such as the "sim-to-real gap" caused by discrepancies between simulated and real-world conditions. Quantitative analysis of planned, simulated, and measured trajectories revealed significant improvements in localization accuracy and trajectory adherence, with Root Mean Square Error (RMSE) values for longitudinal and lateral positions reduced to 0.839 m and 0.1044 m, respectively. Velocity and steering angle tracking demonstrated minor deviations due to actuator constraints and road conditions. This research provides valuable insights into bridging the sim-to-real gap in AEV trajectory planning, paving the way for safer and more reliable autonomous driving systems.

• Ramya, K.; Gopalakrishnan, Janaki; Chokkalingam, Bharatiraja; Verma, Rajesh & Mihet-Popa, Lucian (2025). A Complete Review of Electromagnetic Interference in Electric Vehicle. IEEE Access. doi: 10.1109/ACCESS.2025.3534017. Fulltekst i vitenarkiv
• Mishra, Adesh Kumar; Tripathi, Saurabh Mani; Singh, Omveer; Srivastava, Ankit Kumar; Venkatraman, Thiyagarajan & Vijayaraghavan, Raghavendra Rajan [Vis alle 9 forfattere av denne artikkelen] (2024). Performance assessment of VSC-based HVDC system in asynchronous grid interconnection: Offline and real-time validation of control design with symmetric optimum PI tuning. Heliyon. 10(15). doi: 10.1016/j.heliyon.2024.e35624. Fulltekst i vitenarkiv
• Aravind, R.; Chokkalingam, Bharatiraja; Verma, Rajesh & Mihet-Popa, Lucian (2024). Performance Analysis and Overcoming Cross-Regulation Challenges of a Multi-Input Multi-Output DC-DC Converter for Electric Vehicles. IEEE Access. doi: 10.1109/ACCESS.2024.3480694. Fulltekst i vitenarkiv
• Upadhyay, Saugat; Ahmed, Ibrahim Abbas Elamen & Mihet-Popa, Lucian (2024). Energy Management System for an Industrial Microgrid Using Optimization Algorithms-Based Reinforcement Learning Technique. Energies. 17(16). doi: 10.3390/en17163898. Fulltekst i vitenarkiv Vis sammendrag

  The climate crisis necessitates a global shift to achieve a secure, sustainable, and affordable energy system toward a green energy transition reaching climate neutrality by 2050. Because of this, renewable energy sources have come to the forefront and the research interest in microgrids which rely on distributed generation and storage systems has exploded. Furthermore, many new markets for energy trading, ancillary services, and frequency reserve markets have provided attractive investment opportunities in exchange for balancing the supply and demand of electricity. Artificial intelligence can be utilized to locally optimize energy consumption, trade energy with the main grid, and participate in these markets. Reinforcement learning (RL) is one of the most promising approaches to achieve this goal because it enables an agent to learn optimal behavior in a microgrid by executing specific actions that maximize the long-term reward signal/function. The study focuses on testing two optimization algorithms: logic-based optimization and reinforcement learning. This paper proposes an optimization algorithm based on reinforcement learning in an industrial microgrid that is capable of trading energy with the main grid, providing significant cost savings. The RL-based approach is implemented in Python based on real data from the site and in combination with MATLAB-Simulink to validate its results. The application of the RL algorithm achieved an average monthly cost saving of 20% compared to logic-based optimization and 86% savings compared to not using any optimization. These findings contribute to digitalization and decarbonization of energy technology and support fundamental goals and policies of the European Green Deal.

• Sørensen, Robert & Mihet-Popa, Lucian (2024). Comparative Evaluation of Traditional and Advanced Algorithms for Photovoltaic Systems in Partial Shading Conditions. Solar. 4(4), s. 572–594. doi: 10.3390/solar4040027. Fulltekst i vitenarkiv Vis sammendrag

  The optimization of photovoltaic (PV) systems is vital for enhancing efficiency and economic viability, especially under Partial Shading Conditions (PSCs). This study focuses on the development and comparison of traditional and advanced algorithms, including Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN), for efficient Maximum Power Point Tracking (MPPT). Simulations conducted in the MATLAB/Simulink software package evaluated these algorithms’ performances under various shading scenarios. The results indicate that, while traditional methods like P&O and IC are effective under uniform conditions, advanced techniques, particularly ANN-based MPPT, exhibit superior efficiency and faster convergence under PSCs. This study concludes that integrating Artificial Intelligence (AI) and Machine Learning (ML) into MPPT algorithms significantly enhances the reliability and efficiency of PV systems, paving the way for a broader adoption of solar energy technologies in diverse environmental conditions. These findings contribute to advancing renewable energy technology and supporting green energy transition.

• R, Aravind; Chokkalingam, Bharatiraja; Verma, Rajesh; Aruchamy, Sakthivel & Mihet-Popa, Lucian (2024). Multi-Port Non-Isolated DC-DC Converters and Their Control Techniques for the Applications of Renewable Energy. IEEE Access. 12, s. 88458–88491. doi: 10.1109/ACCESS.2024.3413354. Fulltekst i vitenarkiv
• Ganesan, Manikandan; Kandhasamy, Sivanathan; Chokkalingam, Bharatiraja & Mihet-Popa, Lucian (2024). A Comprehensive Review on Deep Learning-Based Motion Planning and End-to-End Learning for Self-Driving Vehicle. IEEE Access. 12, s. 66031–66067. doi: 10.1109/ACCESS.2024.3394869. Fulltekst i vitenarkiv Vis sammendrag

  Self-Driving Vehicles (SDVs) are increasingly popular, with companies like Google, Uber, and Tesla investing significantly in self-driving technology. These vehicles could transform commuting, offering safer, and efficient transport. A key SDV aspect is motion planning, generating secure, and efficient routes. This ensures safe navigation and prevents collisions with obstacles, pedestrians, and other vehicles. Deep Learning (DL) could aid SDV motion planning. AI tools and algorithms, like Artificial Neural Networks (ANNs), Machine Learning (ML) and DL can learn from data to create effective driving strategies, enhancing SDV adaptability to changing conditions for improved safety and efficiency. This survey gives a DL-based motion planning overview for SDVs, covering behaviour planning, trajectory planning, and End to End Learning (E2EL). It assesses various DL-based behaviour and trajectory planning methods, comparing and summarizing them. It also reviews diverse E2EL techniques including Imitation Learning (IL) and Reinforcement Learning (RL) gaining traction lately. Additionally, this review emphasizes the significance of two crucial enablers: datasets and simulation deployment frameworks for SDVs. The survey compares strategies using multiple metrics and highlights DL-based SDV implementation challenges, including simulation and real-world use cases. This article also suggests future research directions to address E2EL and DL-based motion planning limitations. The presented article is an excellent reference for scholars, engineers, and decision-makers who have an interest in DL-based SDV motion planning.

• S., Devakirubakaran; Verma, Rajesh; Chokkalingam, Bharatiraja & Mihet-Popa, Lucian (2023). Performance Evaluation of Static PV Array Configurations for Mitigating Mismatch Losses. IEEE Access. 11, s. 47725–47749. doi: 10.1109/ACCESS.2023.3274684. Fulltekst i vitenarkiv Vis sammendrag

  Solar photovoltaic (PV) systems are susceptible to power loss caused by environmental factors such as partial shading and temperature changes. To address this issue, PV modules are connected in array configurations. However, these configurations can lead to mismatch losses between the PV rows, which reduce power output. While there are many solutions to mitigate these losses, the performance of each solution can vary depending on the environmental conditions and the array configuration logic. This research paper evaluates the performance of fifteen existing static PV array configuration techniques under various shading patterns. We analyze the mathematical formulation and logic used behind each configuration, as well as the shade dispersion rate, power generation, power losses, advantages, and disadvantages. Our analysis includes a MATLAB/Simulink® model of a 5×5 array for each configuration under different shading patterns. The performance of consistent and best configurations is also evaluated in a real-time environment. The results categorize each configuration as consistent, best, average, or poor. This paper provides a detailed analysis of the different PV array configurations and their performance, which can help in selecting the optimal configuration for specific environmental conditions.

• Rahman, Obaidur; Ali, Arif; Hussain, Ahmad; Khan, Shakeb Ahmad; Tariq, Mohd & Urooj, Shabana [Vis alle 8 forfattere av denne artikkelen] (2023). Investigation of CeO2 Nanoparticles on the Performance En-hancement of Insulating Oils. Heliyon. 9(9). doi: 10.1016/j.heliyon.2023.e19264. Fulltekst i vitenarkiv Vis sammendrag

  Integrating nanotechnology in dielectric fluid significantly inhibits losses and boosts overall dielectric fluid performance. There has been research done on the effects of introducing various nanoparticles, such as titania, alumina, silica nanodiamonds, etc. In this paper, a novel nanoparticle, Ceria (CeO2), has been used, and its properties were examined using the FTIR (Fourier Transform Infrared) spectrum, the XRD (X-ray Diffrac-tion) spectrum, the SEM (Scanning Electron Microscopy), and the TEM (Transmission Electron Microscopy). This paper illustrates an efficient dielectric fluid prepared by the successful dispersion of Cerium Oxide (CeO2) nanoparticles in various concentrations into four commercial oils, namely mineral oil, rapeseed oil, synthetic ester oil, and soybean oil, to enhance and improve their dielectric characteristics. The performance investigation emphasises breakdown strength enhancement and other dielectric properties of the colloidal solution comprising different nanoparticle (NP) concentrations. Various commercial oils are used as a base in nano-oil to diversify their applicability as dielectric fluids by measuring the correlation in dielectric parame-ters and statistically assessing their applicability with normal and Weibull distributions. The obtained ex-perimental data sets were analysed using the Statistics and Machine Learning Toolbox in MATLAB. The aging measurement has been done only on mineral oil, and results were matched using a predictive model of statistics and the Machine Learning Toolbox in MATLAB. Well-dispersed CeO2 NPs in the insulating oils lead to a significant increase in AC breakdown strength. The effect of ageing on the dielectric properties of nano oils yields better results than conventionally aged oil. It has been observed that the breakdown voltage is enhanced by up to 30 % for mineral oil at an optimal concentration of 0.01 g/L, 9% for synthetic ester oil at 0.03 g/L, 18% for rapeseed oil at 0.02 g/L, and 19% for soybean oil at 0.03 g/L nanoparticle concentration. Following the dispersion of CeO2 nanoparticles, the dielectric constant of all insulating oils has also signifi-cantly improved. The overall experimental results are promising and show the potential of the CeO2 NPs-based nano oil as an efficient and highly performing dielectric oil for different power applications.

• Jeyaraj, Pandia Rajan; Nadar, Edward & Mihet-Popa, Lucian (2023). Deep-Block Network for Cyberattack Mitigation and Assessment in Smart Grid Power System with Resilience Indices. Electric power components and systems. ISSN 1532-5008. 51(0). doi: 10.1080/15325008.2023.2268073. Fulltekst i vitenarkiv Vis sammendrag

  Distributed renewable energy sources, with widecommunication components in a microgrid infrastructure, makecyber security assessment and mitigation a developing cyber-physical system study. Extensive cybersecurity threads areprevailing in modernized smart grid. Hence, to detect and mitigatecyber threads an advanced cost-effective resilience cyber riskassessment and mitigation mechanism is needed. To enhancecyber-physical security in smart grids, a secured deep learningalgorithm with blockchain technology (BlockDeepNet) isproposed. Distributed secured data analysis is carried by usingdeep learning approach, while blockchain helps in theimplementation of secured decentralized resilient control. Tovalidate, real-time cosimulation on IEEE 15 bus system wasconducted. Also, for evaluating cyber security breach, four typesof cyberattacks were introduced to validate the effectiveness ofproposed security assessment and resilience operation. Weobtained normalized resilience indexkR1k2of 2.36 for gridcommunication failure, 0.91 for replay attack, 1.34 for false datainjection, and 1.74 for DoS attack. The obtained results onsimulation case study by real-time hardware in the loopimplementation showed that the proposed BlockDeepNetaccurately reduce load loss for various cyberattack and providerobust resiliency. Overall, this research provides a platform forcybersecurity assessment and enhanced resilience operation ofcyber-physical power energy system.

• R, Ranjith Kumar; Chokkalingam, Bharatiraja; K, Udhayakumar; S, Deva Kirubakaran; Sekar, Sathiya & Mihet-Popa, Lucian (2023). Advances in Batteries, Battery Modeling, Battery Management System, Battery Thermal Management, SOC, SOH, and Charge/Discharge Characteristics in EV Applications. IEEE Access. 11, s. 105761–105809. doi: 10.1109/ACCESS.2023.3318121. Fulltekst i vitenarkiv Vis sammendrag

  The second-generation hybrid and Electric Vehicles are currently leading the paradigm shift in the automobile industry, replacing conventional diesel and gasoline-powered vehicles. The Battery Management System is crucial in these electric vehicles and also essential for renewable energy storage systems. This review paper focuses on batteries and addresses concerns, difficulties, and solutions associated with them. It explores key technologies of Battery Management System, including battery modeling, state estimation, and battery charging. A thorough analysis of numerous battery models, including electric, thermal, and electro-thermal models, is provided in the article. Additionally, it surveys battery state estimations for a charge and health. Furthermore, the different battery charging approaches and optimization methods are discussed. The Battery Management System performs a wide range of tasks, including as monitoring voltage and current, estimating charge and discharge, equalizing and protecting the battery, managing temperature conditions, and managing battery data. It also looks at various cell balancing circuit types, current and voltage stressors, control reliability, power loss, efficiency, as well as their advantages and disadvantages. The paper also discusses research gaps in battery management systems.

• Jasim, Ali M.; Jasim, Basil H.; Flah, Aymen; Bolshev, Vadim & Mihet-Popa, Lucian (2023). A new optimized demand management system for smart grid-based residential buildings adopting renewable and storage energies. Energy Reports. 9, s. 4018–4035. doi: 10.1016/j.egyr.2023.03.038. Fulltekst i vitenarkiv Vis sammendrag

  Demand Side Management (DSM) implies intelligently managing load appliances in a Smart Grid (SG). DSM programs help customers save money by reducing their electricity bills, minimizing the utility’s peak demand, and improving load factor. To achieve these goals, this paper proposes a new load shifting-based optimal DSM model for scheduling residential users’ appliances. The proposed system effectively handles the challenges raised in the literature regarding the absence of using recent, easy, and more robust optimization techniques, a comparison procedure with well-established ones, using Renewable Energy Resources (RERs), Renewable Energy Storage (RES), and adopting consumer comfort. This system uses recent algorithms called Virulence Optimization Algorithm (VOA) and Earth Worm Optimization Algorithm (EWOA) for optimally shifting the time slots of shiftable appliances. The system adopts RERs, RES, as well as utility grid energy for supplying load appliances. This system takes into account user preferences, timing factors for each appliance, and a pricing signal for relocating shiftable appliances to flatten the energy demand profile. In order to figure out how much electricity users will have to pay, a Time Of Use (TOU) dynamic pricing scheme has been used. Using MATLAB simulation environment, we have made effectiveness-based comparisons of the adopted optimization algorithms with the well-established meta-heuristics and evolutionary algorithms (Genetic Algorithm (GA), Cuckoo Search Optimization (CSO), and Binary Particle Swarm Optimization (BPSO) in order to determine the most efficient one. Without adopting RES, the results indicate that VOA outperforms the other algorithms. The VOA enables 59% minimization in Peak-to-Average Ratio (PAR) of consumption energy and is more robust than other competitors. By incorporating RES, the EWOA, alongside the VOA, provides less deviation and a lower PAR. The VOA saves 76.19% of PAR, and the EWOA saves 73.8%, followed by the BPSO, GA, and CSO, respectively. The electricity consumption using VOA and EWOA-based DSM cost 217 and 210 USD cents, respectively, whereas non-scheduled consumption costs 273 USD cents and scheduling based on BPSO, GA, and CSO costs 219, 220, and 222 USD cents.

• Ali, Muhammad; Farooq, Ajmal; Khan, Muhammad Qasim; Khan, Muhammad Mansoor & Mihet-Popa, Lucian (2023). Analysis of Asymmetric Hybrid Modular Multilevel Topology for Medium-Voltage Front-End Converter Applications. Energies. 16(4). doi: 10.3390/en16041572. Fulltekst i vitenarkiv
• Ramu, Priyadharshini; Gangatharan, Sivasankar; Rangasamy, Sankar & Mihet-Popa, Lucian (2023). Categorization of Loads in Educational Institutions to Effectively Manage Peak Demand and Minimize Energy Cost Using an Intelligent Load Management Technique. Sustainability. 15(16). doi: 10.3390/su151612209. Fulltekst i vitenarkiv
• R, Priyadharshini Ramu; Gangatharan, Sivasankar; Rangasamy, Sankar & Mihet-Popa, Lucian (2023). Categorization of Loads in Educational Institutions to Effectively Manage Peak Demand and Minimize Energy Cost Using Intelligent Load Management Technique. Sustainability. Fulltekst i vitenarkiv
• Mihet-Popa, Lucian; Ahmed, Ibrahim & Pedersen, Andreas (2023). Hierarchical Control of an Islanded AC Micro Grid Using FS-MPC and an EMS. I Mihet-Popa, Lucian (Red.), SMART GRIDS TECHNOLOGY AND APPLICATIONS. IntechOpen. ISSN 9781803556857. s. 20–47. doi: 10.5772/intechopen.110815. Fulltekst i vitenarkiv Vis sammendrag

  Microgrids and distributed energy resources (DERs) are gaining popularity owing to their efficient operation, autonomy, and dependability. Microgrids provide several new opportunities, one of which is the ability to deliver electricity continuously, even in the event of a grid failure. This chapter will first describe the modeling of DER components in a microgrid, with each component using Finite Set-Model Predictive Control (FS-MPC) for controlling the inverters to be robust, to have a fast response, to account for multiple objectives, and to eliminate manual tuning. In addition, droop control will be used to provide a voltage reference for the FS-MPC. The PV-inverter will operate as a grid- forming inverter, while the other inverters will serve as grid-feeding inverters. The proposed inverter models are validated using simulations. The microgrid has been modeled using MATLAB-Simulink software package. A supervisory controller for energy management system of the microgrid to operate in different power flows through the proposed control algorithm has also been designed. The simulation results show the effectiveness and robustness of the proposed controller during dynamic performance and transients, and the developed energy management system algorithm successfully controlled the power flow to ensure continuous power delivery to the load under all circumstances.

• Kumar, V. Manoj; Chokkalingham, Bharatiraja & Mihet-Popa, Lucian (2023). Mitigation of Complexity in Charging Station Allocation for EVs Using Chaotic Harris Hawks Optimization Charge Scheduling Algorithm. IEEE Access. 11, s. 130466–130482. doi: 10.1109/ACCESS.2023.3334672. Fulltekst i vitenarkiv Vis sammendrag

  The development of EV technology and EV migration is limited by various factors such as sizing of batteries, short driving ranges, optimal operations, and so on. The EV charging faces many difficulties such as waiting time, charging time, uneven charge scheduling, and uneven distributed charging stations. In Charging Station (CS), EVs usually spend much time in queues, mainly during peak hours of charging. Therefore, building a well-established charging station network should be derived from charging demand and proper charge scheduling to assist EVs for getting charged with less cost, less waiting time. Also, it should reduce the number of vehicles scheduling during the peak load time. This work aims to design a scheduling system for EV charging using an optimization strategy of Chaotic Harris Hawks optimization (CHHO) which reduces the total time spent on charging station and the distance of EV origin to destination. CHHO is authenticated using Vehicular Ad-hoc Network (VANET) simulation, and the performances are compared with algorithms Exponential Harris Hawk Optimization, Grey Wolf Optimizer, First in First Out and Random Allocation to demonstrate the efficacy of our technique. The proposed CHHO-based scheduling system yields better performance with the maximum remaining energy and significantly cuts the average travel time, and improves the utilization rate of EVs in charging stations compared to other algorithms. A detailed result and discussions on different case studies by varying number of vehicles and number of charging stations and the corresponding average waiting time were obtained and presented in this paper.

• Aravind, R.; Chokkalingam, Bharatiraja & Mihet-Popa, Lucian (2023). A Transformerless Non-Isolated Multi-Port DC-DC Converter for Hybrid Energy Applications. IEEE Access. 11, s. 52050–52065. doi: 10.1109/ACCESS.2023.3280195. Fulltekst i vitenarkiv Vis sammendrag

  This paper presents a novel high-gain non-isolated Four Port DC-DC converter (FPC) topology for hybrid energy applications. The proposed four-port dc-dc converter interfaces four power ports of three input ports and one output port. High output voltage gain, minimized component count, and high efficiency are the advantages of the proposed converter, which renders it very useful for hybrid energy applications such as fast-charging electric vehicles. The high output voltage gain of the proposed FPC is achieved by the Actively Switched Inductor Capacitor (ALC) network. Moreover, the reduction in component count is achieved by minimizing the number of switches per input port. This enhances the converter efficiency is 96.77 % with a voltage gain 4.75. In this study, the FPC topology and modes of operation are described along with complete, steady state analysis, loss analysis, and switch voltage stress (VS) analysis of the converter. The converter operates in five modes, where all three sources can either be interfaced with the load by simply altering the switching patterns. Circuit topology, modes of operation, circuit analysis simulation, and real-time validations have been described in this paper.

• CHITTOOR, PRITHVI KRISHNA; Chokkalingam, Bharatiraja; Verma, Rajesh & Mihet-Popa, Lucian (2023). An Assessment of Shortest Prioritized Path-Based Bidirectional Wireless Charging Approach Toward Smart Agriculture. IEEE Access. 11, s. 123742–123755. doi: 10.1109/ACCESS.2023.3329976. Fulltekst i vitenarkiv Vis sammendrag

  The agriculture sector has witnessed a transformation with the advent of smart sensing devices, leading to improved crop yield and quality. However, the management of data collection from numerous sensors across vast agricultural areas, as well as the associated charging requirements, presents significant challenges. This paper addresses the major research problem by proposing an innovative solution for charging agricultural sensors. The introduction of an energy-constrained device (ECD) enables wireless charging and transmission of soil data to a centralized server. The proposed ECDs will enable enhanced data collection, precision agriculture, optimized resource allocation, timely decision-making, and remote monitoring and control. A bidirectional wireless charging drone is employed to efficiently charge the ECDs. To optimize energy usage, a prioritized Dijkstra algorithm determines the ECDs to be charged and plans the shortest route for the drone. The wireless charging drone landing-charging station achieves an efficiency of 91.3%, delivering 72 W of power within a 5 mm range. Furthermore, the ECD possesses a data transmission range of 100 m and incorporates deep sleep functionality, allowing for a remarkable 30-day battery life.

• Srilakshmi, Koganti; Sujatha, Canavoy Narahari; Balachandran, Praveen Kumar; Mihet-Popa, Lucian & Kumar, Naluguru Udaya (2022). Optimal Design of an Artificial Intelligence Controller for Solar-Battery Integrated UPQC in Three Phase Distribution Networks. Sustainability. 14(21). doi: 10.3390/su142113992. Fulltekst i vitenarkiv
• Khan, Suhaib Ahmad; Tariq, Mohd; Khan, Asfar Ali; Alamri, Basem & Mihet-Popa, Lucian (2022). Assessment of Thermo-Physical Performance of Ester-Based Nanofluids for Enhanced Insulation Cooling in Transformers. Electronics (Basel). 11(3). doi: 10.3390/electronics11030376. Fulltekst i vitenarkiv Vis sammendrag

  Nanotechnology provides an effective way to upgrade the thermo physical characteris- 12 tics of dielectric oils and creates optimal transformer design. The properties of insulation materials 13 have a significant effect on the optimal transformer design. Ester based nanofluids (NF) are intro- 14 duced as an energy-efficient alternative to conventional mineral oils, and prepared by dispersing 15 nanoparticles in the base oil. This study presents the effect of nanoparticles on the thermo-physical 16 properties of pure natural ester (NE) and synthetic ester (SE) oils with temperature varied from 17 ambient up to 80 oC. A range of concentrations of Graphene oxide (GO) and TiO2 nanoparticles 18 were used in the study to upgrade the thermo physical properties of ester based oils. The experi- 19 ment for thermal conductivity and viscosity were performed using a TC-4 apparatus that follows 20 Debby’s concept, and redwood viscometer apparatus that follows the ASTM- D445 experimental 21 standard respectively. The experimental results show that nanoparticles have a positive effect on 22 thermal conductivity and viscosity of oils, while they reduce with increase in temperature

• Vankadara, Sampath Kumar; Chatterjee, Shamik; Balachandran, Praveen Kumar & Mihet-Popa, Lucian (2022). Marine Predator Algorithm (MPA)-Based MPPT Technique for Solar PV Systems under Partial Shading Conditions. Energies. 15(17). doi: 10.3390/en15176172. Fulltekst i vitenarkiv Vis sammendrag

  To satisfy global electrical energy requirements, photovoltaic (PV) energy is a promising source that can be obtained from the available alternative sources, but partial shading conditions (PSCs), which trap the local maxima power point instead of the global maxima peak power point (GMPP), are a major problem that needs to be addressed in PV systems to achieve the uninterruptable continuous power supply desired by consumers. To avoid these difficulties, a marine predator algorithm (MPA), which is a bio-inspired meta-heuristic algorithm, is applied in this work. The work is validated and executed using MATLAB/Simulink software along with hardware experimentation. The superiority of the proposed MPA method is validated using four different PSCs on the PV system, and their characteristics are compared to those of existing algorithms. The four different PSC outcomes in terms of GMPP are case 1 at 0.07 s 995.0 Watts; case 2 at 0.06 s 674.5 Watts; case 3 at 0.04 s 654.1 Watts; and case 4 at 0.04 s 364.2 Watts. The software- and hardware-validated results of the proposed MPA method show its supremacy in terms of convergence time, efficiency, accuracy, and extracted power.

• Khatoon, Shabana; Khan, Asfar Ali; Tariq, Mohd; Alamri, Basem & Mihet-Popa, Lucian (2022). Flashover Voltage Prediction Models under Agricultural and Biological Contaminated Condition on Insulators. Energies. 15(4). doi: 10.3390/en15041297. Fulltekst i vitenarkiv Vis sammendrag

  The flashover performance of contaminated insulators highly depends on the type of pollutant and its present concentration. In this paper, important agricultural salts (NaCl, K2SO4, NaHCO3, CaSO4, KHCO3, MgSO4, NH4), 2Fe (SO4)2 , 6H2O (ferrous ammonium sulphate, dust and urea) at different concentration and biological contaminants such as algae and fungi were taken as pollutants, and AC flashover behaviour of porcelain cap and pin type insulator polluted with these two different pollutants was investigated. The experiment was carried out by a semi-natural method wherein the insulator was first polluted artificially thereafter natural fog was applied to measure the wet flashover voltage. Test results indicate that the flashover voltages were affected by both soluble salts and non-soluble components deposit on the insulator surface. In case of thick contaminated layer non-soluble deposits greatly reduced the flashover voltage. Moreover, by using regression analysis four empirical models based on different variables have been developed. The empirical models developed in the present work represent a good degree of relation to predicting the flash-over voltage of naturally contaminated insulators.

• Riaz, Muhammad; Ahmad, Sadiq; Hussain, Irshad; Naeem, Muhammad Asif & Mihet-Popa, Lucian (2022). Probabilistic Optimization Techniques in Smart Power System. Energies. 15(3). doi: 10.3390/en15030825. Fulltekst i vitenarkiv Vis sammendrag

  Uncertainties are the most significant challenges in the smart power system, necessitating the use of precise techniques to deal with them properly. Such problems could be effectively solved using a probabilistic optimization strategy. It is further divided into stochastic, robust, distributionally robust, and chance-constrained optimizations. The topics of probabilistic optimization in smart power systems are covered in this review paper. In order to account for uncertainty in optimization processes, stochastic optimization is essential. Robust optimization is the most advanced approach to optimize a system under uncertainty, in which a deterministic, set-based uncertainty model is used instead of a stochastic one. The computational complexity of stochastic programming and the conservativeness of robust optimization are both reduced by distributionally robust optimization.Chance constrained algorithms help in solving the constraints optimization problems, where finite probability get violated. This review paper discusses microgrid and home energy management, demand-side management, unit commitment, microgrid integration, and economic dispatch as examples of applications of these techniques in smart power systems. Probabilistic mathematical models of different scenarios, for which deterministic approaches have been used in the literature, are also presented. Future research directions in a variety of smart power system domains are also presented.

• Rajamoorthy, Rajasekaran; Saraswathi, Hemachandira V.; Devaraj, Jayanthi; Kasinathan, Padmanathan; Elavarasan, Rajvikram Madurai & Arunachalam, Gokulalakshmi [Vis alle 8 forfattere av denne artikkelen] (2022). A Hybrid Sailfish Whale Optimization and Deep Long Short-Term Memory (SWO-DLSTM) Model for Energy Efficient Autonomy in India by 2048. Sustainability. 14(3). doi: 10.3390/su14031355. Fulltekst i vitenarkiv Vis sammendrag

  In order to formulate the long-term and short-term development plans to meet the energy needs, there is a great demand for accurate energy forecasting. Most of the existing energy demand forecasting models predict the amount of energy at a regional or national scale and failed to forecast the demand for power generation for small-scale decentralized energy systems, like micro grids, buildings, and energy communities. Deep learning models play a vital role in accurately forecasting the energy de-mand. A novel model called Sail Fish Whale Optimization-based Deep Long Short- Term memory (SFWO-based Deep LSTM) to forecast electricity demand in the distribution systems is proposed. The proposed SFWO is designed by integrating the Sail Fish Optimizer (SFO) with the Whale Optimiza-tion Algorithm (WOA). The Hilbert-Schmidt Independence Criterion Lasso (HSIC) is applied on the dataset, which is collected from the Central electricity authority, Government of India, for selecting the optimal features using the technical indicators. The proposed algorithm was implemented in MATLAB software package and the study was done using real-time data. The feature selection pro-cess improves the accuracy of the proposed model by training the features using Deep LSTM. The results of the proposed model in terms of install capacity prediction, village electrified prediction, length of R & D lines prediction, hydro, coal, diesel, nuclear prediction, etc. are compared with the existing models. The proposed model achieves good accuracy with the average normalized Root Mean Squared Error (RMSE) value of 4.4559. The hybrid approach provides improved accuracy for the prediction of energy demand in India by the year 2047.

• Mohanraj, Deepak; Aruldavid, Ranjeev; Verma, Rajesh; Sathiyasekar, K.; Barnawi, Abdulwasa B. & Chokkalingam, Bharatiraja [Vis alle 7 forfattere av denne artikkelen] (2022). A Review of BLDC Motor: State of Art, Advanced Control Techniques, and Applications. IEEE Access. 10, s. 54833–54869. doi: 10.1109/ACCESS.2022.3175011. Fulltekst i vitenarkiv Vis sammendrag

  The shortage of biofuel and the high tailpipe emission from vehicles demand the adoption of green energy. The development of Electric Vehicles (EVs) represents a watershed moment in the effort to go green. The EVs have a low mileage range and are expensive due to the sophisticated design and control mechanism of motors, which has hampered their popularity. Recently the interest in developing the new age EV grade motors with high dynamic characteristics is increased. This paper reviews the recent advancements in EV motors, Control techniques, and the challenges of various e-motors. The technical performance and cost of different electric motors (e-motors) used in EVs are compared, and the challenges are listed. The Permanent magnet brushless DC motor (PMBLDC) provides high torque density, Permanent magnet synchronous motor (PMSM) delivers high efficiency, and switched reluctance motor (SRM) has a low cost however all of these have high torque ripple, and though the Induction motor (IM) has the advantage of low ripple and low cost, nevertheless the efficiency is poor. In addition to a detailed electric motor (e-motor) design process, future research possibilities in achieving long-range and low costs are also stated.

• Khan, Suhaib Ahmad; Tariq, Mohd; Khan, Asfar Ali; Urooj, Shabana & Mihet-Popa, Lucian (2022). An Experimental Study and Statistical Analysis on the Dielectric Properties of ZnO and CuO-Based Synthetic Ester Nanofluids. Energies. 15(23). doi: 10.3390/en15239127. Fulltekst i vitenarkiv
• Badini, Sai Shiva; Verma, Vimlesh; Tariq, Mohd; Urooj, Shabana & Mihet-Popa, Lucian (2022). Performance of a Vector-Controlled PMSM Drive without Using Current Sensors. Mathematics. 10(23). doi: 10.3390/math10234623. Fulltekst i vitenarkiv Vis sammendrag

  The current sensorless vector-controlled permanent-magnet synchronous motor (PMSM) drive using a single sensor (i.e., speed sensor) is presented in this work. The current sensors are removed, and the estimated currents are used to close the current loop to minimize the drive cost and make it fault-tolerant against current sensor failure. A classical vector-control PMSM drive requires at least three sensors, i.e., two current sensors and one speed/position sensor. This paper presents a new current estimation technique that is free from inverter switching states, an integrator, and differentiator terms. The drive is suitable for retrofit applications, as it does not require any additional hardware. The reference voltages (vds and vqs) are used to estimate the rotor reference frame currents (i.e., iqs and ids). The presented algorithm depends on the stator resistance (Ɍs). The online Ɍs estimation algorithm is used for compensation to overcome the effect of the Ɍs on the estimated currents. The sensitivity analysis for the currents against the speed is verified and presented. The speed loop is closed with actual speed information, which will try to maintain the reference speed under any circumstances. The proposed current sensorless PMSM drive was validated using MATLAB/Simulink and also verified on a hardware prototype. The presented technique was verified for various operation conditions, and some of the extensive results are presented.

• Srivastava, Ankit Kumar; Tripathi, Saurabh Mani; Kumar, Sachin; Elavarasan, Rajvikram Madurai; Gangatharan, Sivasankar & Kumar, Dinesh [Vis alle 7 forfattere av denne artikkelen] (2022). Machine Learning Approach for Forecast Analysis of Novel COVID-19 Scenarios in India. IEEE Access. 10, s. 95106–95124. doi: 10.1109/ACCESS.2022.3204804. Fulltekst i vitenarkiv Vis sammendrag

  The novel coronavirus (nCOV) is a new strain that needs to be hindered from spreading by taking effective preventive measures as swiftly as possible. Timely forecasting of COVID-19 cases can ultimately support in making significant decisions and planning for implementing preventive measures. In this study, three common machine learning (ML) approaches via linear regression (LR), sequential minimal optimization (SMO) regression, and M5P techniques have been discussed and implemented for forecasting novel coronavirus disease-2019 (COVID-19) pandemic scenarios. To demonstrate the forecast accuracy of the aforementioned ML approaches, a preliminary sample-study has been conducted on the first wave of the COVID-19 pandemic scenario for three different countries including the United States of America (USA), Italy, and Australia. Furthermore, the contributions of this study are extended by conducting an in-depth forecast study on COVID-19 pandemic scenarios for the first, second, and third waves in India. An accurate forecasting model has been proposed, which has been constructed on the basis of the results of the aforementioned forecasting models of COVID-19 pandemic scenarios. The findings of the research highlight that LR is a potential approach that outperforms all other forecasting models tested herein in the present COVID-19 pandemic scenario. Finally, the LR approach has been used to forecast the likely onset of the fourth wave of COVID-19 in India.

• Indrajayanthan, Venkatraman; Mohanty, Nalin Kant; Elavarasan, Rajvikram Madurai & Mihet-Popa, Lucian (2022). Investigation on current and prospective energy transition scenario in Indian landscape using integrated SWOT-MCDA methodology. Sustainability. 14(9). doi: 10.3390/su14094940. Fulltekst i vitenarkiv Vis sammendrag

  India has ambitious goals to increase renewable energy penetration and significant progress have been made since 2017. However, the Indian energy mix is highly dominated by fossil fuels. To set India in the pathway of the energy transition, a comprehensive analysis of complex factors influencing the Indian energy sector is required. This study is put forward to delineate the current scenario of energy transition in India and to direct the energy sector towards a prospective scenario for accomplishing a smooth energy transition. A hybrid quantitative-qualitative SWOT integrated MCDA methodology is employed to accomplish the objective of this study. An extensive literature review is performed to understand and sort the various factors under each SWOT category. Fuzzy AHP methodology is utilized to convert the qualitative significance of each SWOT factor into quantitative scores through which the crucial influencing factor in the current energy transition scenario is obtained. The top three highest influencing factors include utilizing the cost-competitiveness of solar and wind energy technologies over fossil fuels, the inadequacy of manpower having specialized skillsets, and connecting households to electricity and electrifying the transportation sector. The recommendation strategies are framed and presented for prospective energy transition scenario. These strategies are assessed against the SWOT factors by using the PROMETHEE II methodology. The assessment results highlight that developing robust regulatory and policy frameworks, increasing the contribution of local energy resources, and promoting the distributed generation and grid infrastructure development are the highest scoring strategies that have a synergic effect on multiple dimensions of energy transition including political, financial and techno-economic aspects. The proposed study will be conducive to framing effective policy in the upcoming years to assist the energy transition in India.

• Repalle, Naveena Bhargavi; Sarala, Pullacheri; Mihet-Popa, Lucian; Kotha, Shashidhar Reddy & Rajeswaran, Nagalingam (2022). Implementation of a Novel Tabu Search Optimization Algorithm to Extract Parasitic Parameters of Solar Panel. Energies. 15(13). doi: 10.3390/en15134515. Fulltekst i vitenarkiv Vis sammendrag

  : The aging of PV cells reduces their electrical performance i.e., the parasitic parameters are introduced in the solar panel. The shunt resistance (RSh), series resistance (RS), photo current (IPh), diode current (Id), and diffusion constant (a1) are known as parasitic or extraction parameters. Cracks and hotspots reduce the performance of PV cells and result in poor V–I characteristics. Certain tests are carried out over a long period of time to determine the quality of solar cells; for example, 1000 h of testing is comparable to 20 years of operation. The extraction of solar parameters is important for PV modules. The Tabu Search Optimization (TSO) algorithm is a robust meta-heuristic algorithm that was employed in this study for the extraction of parasitic parameters. Particle Swarm Optimization (PSO) and a Genetic lgorithm (GA), as well as other well-known optimization methods, were used to test the proposed method's correctness. The other approaches included the lightning search algorithm (LSA), gravitational search algorithm (GSA), and pattern search (PS). It can be concluded that the TSO approach extracts all six parameters in a reasonably short period of time. The work presented in this paper was developed and analyzed using a MATLAB-Simulink software environment.

• Mohanraj, Deepak; Gopalakrishnan, Janaki; Chokkalingam, Bharatiraja & Mihet-Popa, Lucian (2022). Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review. IEEE Access. 10, s. 73635–73674. doi: 10.1109/ACCESS.2022.3187515. Fulltekst i vitenarkiv Vis sammendrag

  Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.

• Rajeswaran, Nagalingam; Rajesh, Thangaraj; Mihet-Popa, Lucian; Krishna, K.Vamshi & Özer, Özen (2022). FPGA Implementation of AI-Based Inverter IGBT Open Circuit Fault Diagnosis of Induction Motor Drives. Micromachines. 13(5). doi: 10.3390/mi13050663. Fulltekst i vitenarkiv Vis sammendrag

  In modern industrial manufacturing processes, induction motors are broadly utilized as industrial drives. Online condition monitoring and diagnosis of faults that occur inside and/or outside of the Induction Motor Drive (IMD) system makes the motor highly reliable, helping to avoid unsched-uled downtimes, which cause more revenue loss and disruption of production, thus making it as the extensively used industrial drive. This can be achieved only when the irregularities produced out of the fault circumstance are sensed at that instant itself and diagnosed as to what and where happened for suitable action by the protective equipment employed. This requires intelligent control with high performance scheme. Hence, Field Programmable Gate Array (FPGA) based Neuro-Genetic implementation with Back Propagation Neural Network (BPN) is suggested in this article to diagnose the fault more efficiently and almost instantly. It is reported that the classifica-tion of neural network will provide the output within 2 µs although the clone procedure with mi-crocontroller requires 7 ms. This intelligent control with high performance technique is applied to the IMD fed by Voltage Source Inverter (VSI) to diagnose the fault external to the induction motor occurring in the VSI supply system. The proposed approach was simulated and experimentally validated.

• Elavarasan, Rajvikram Madurai; Pugazhendhi, Rishi; Irfan, Muhammad; Mihet-Popa, Lucian; Khan, Irfan Ahmad & Campana, Pietro Elia (2022). State-of-the-art sustainable approaches for deeper decarbonization in Europe – An endowment to climate neutral vision. Renewable and Sustainable Energy Reviews. ISSN 1364-0321. doi: 10.1016/j.rser.2022.112204. Fulltekst i vitenarkiv Vis sammendrag

  This study reviews the effective decarbonization strategies in the context of Europe’s climate neutral vision. Initially, the study analyzes the reasons for ever-increasing emissions and investigates the perception of decarbonization in line with various influencing factors such as population size, economic growth, energy intensity, emission intensity, innovation, affordability and time. Subsequently, an in-depth qualitative analysis is performed to force out challenges that Europe faces in decarbonizing the heating sector from the aspects, such as using clean energy resources, effective heat energy conversion and management approaches. Sustainable approaches and practices are proposed to mitigate carbonization and to promote carbon sink in line with the major problems associated with various sectors. This study also reviews various decarbonization policies that can direct the governments’ action to effectively make a transition towards a climate-neutral society. The key findings highlight that solar energy utilization in small-scale is relatively not preferable for heat energy conversion due to climatic conditions, while district heating network with bio- and geothermal energy resource highly favors clean heat transformation scenario. In addition, 3D printing has a prodigious role to reduce building lifecycle emissions and hybrid policies as well as reward-based policies yields better outcomes. Promoting hydrogen utilization and carbon capture storage and utilization technologies can pivot climate neutrality in the sectors that are difficult to decarbonize. On the other hand, it can be observed that more focus is provided to reduce emissions and significantly less attention is focused on carbon sink.

• Khan, Suhaib Ahmad; Tariq, Mohd; Khan, Asfar Ali; Urooj, Shabana & Mihet-Popa, Lucian (2022). An Experimental Study and Statistical Analysis on the Electrical Properties of Synthetic Ester-Based Nanofluids. Energies. 15(23). doi: 10.3390/en15239127. Fulltekst i vitenarkiv Vis sammendrag

  The rise in power demand today necessitates its generation and transmission at high voltages. The efficient transmission of electric power requires transformers with an insulation system that exhibits excellent dielectric properties. In this paper ZnO and CuO nanomaterials are utilized to investigate the dielectric characteristics of pure synthetic ester oil and its related nanofluids (NFs) from room temperature up to 60 °C at increments of 20 °C, including AC breakdown voltage, Dielectric Dissipation factor, and DC resistivity. The breakdown testing is carried out in accordance with experimental IEC-60156 requirements. The DC resistivity and dissipation factor of oils are measured using the Dissipation Factor meter, resistivity meter, and a heating chamber with an oil cell that follows IEC 60247 standard. The statistical analysis is performed on the breakdown voltages test values using the Weibull probability distribution model for better accuracy. From the results, it has been found that ZnO nanofluid possesses a higher breakdown voltage among all the tested liquids. Furthermore CuO nanofluid gives a minimum value of dissipation factor even at higher temperatures.

• Alwar, Srinivasan; Samithas, Devakirubakaran; Boominathan, Meenakshi Sundaram; Balachandran, Praveen Kumar & Mihet-Popa, Lucian (2022). Performance Analysis of Thermal Image Processing-Based Photovoltaic Fault Detection and PV Array Reconfiguration—A Detailed Experimentation. Energies. 15(22). doi: 10.3390/en15228450. Fulltekst i vitenarkiv Vis sammendrag

  Due to the flexibility, sustainability, affordability, and ease of installation of solar photovoltaic systems, their use has significantly increased over the past two decades. The performance of a solar PV system can be constrained by a variety of external conditions, including hotspots, partial shade, and other minor faults. This causes the PV system to permanently fail and power losses. The power output in a partially shaded solar system is improved in this work by the introduction of a fault classifier based on thermal image analysis with a reconfiguration algorithm. For that purpose, the entire PV array is divided into two parts, with one of these being the male part and the other being the female part. MOSFET switches are used to build the switching matrix circuit that connects these parts. The Flir T420bx thermal camera captures thermal pictures, and MATLAB/Simulink® is used to extract the image properties. The pairing reconfiguration pattern is found using an algorithm based on image processing and the image attributes. The switching signals to the switching circuit are triggered by an Arduino controller. The image attributes of the thermal images may also be used to categorize PV system defects. This reconfiguration technique is easy, simple to use, and it can also be used to check the health of each PV module. The performance of the proposed work was validated using a 5 kW PV system with a 4 × 5 TCT array configuration at Sethu Institute of Technology’s renewable energy lab in India. The proposed method was simulated using the MATLAB-Simulink software program, and the outcomes were verified on different hardware setups.

• Harini, S.; Chellammal, N.; Chokkalingam, Bharatiraja & Mihet-Popa, Lucian (2022). A Novel High Gain Dual Input Single Output Z-Quasi Resonant (ZQR) DC/DC Converter for Off-Board EV Charging. IEEE Access. 10, s. 83350–83367. doi: 10.1109/ACCESS.2022.3195936. Fulltekst i vitenarkiv Vis sammendrag

  This manuscript focuses on a Multi-port non-isolated (Dual input and single output) DC/DC power electronic interface based on Z-Quasi resonant (ZQR) network. The converter accommodates grid and Photovoltaic panel (PV) as its input sources. Unlike the basic DC/DC converters, the recommended DC/DC converter requires fewer switches and provides continuous current, high voltage gain, and minimal voltage stress on converter switch up to 40% duty cycle owing to the presence of ZQR network. This feature of the converter makes it suitable for applications like Electric Vehicle (EV) off-board charging, where a high voltage gain is required. The purpose of this paper is to develop and evaluate a multi-port ZQR DC/DC converter for EVs. In the proposed multi-port ZQR converter, additional input and output ports could be appended without compromising the converter's gain and efficiency. The developed converter can operate continuously even if any one of the input sources fails to charge the EV. The proposed converter is mathematically modeled using basic laws that govern the converter performance and analyzed in MATLAB Simulink platform under various operating modes. A detailed analysis under steady-state and dynamic conditions as well as a comparison of the developed multiport ZQR DC/DC converter with the topologies addressed in published literature are also presented in this manuscript. In order to verify the proposed converter performance, a prototype model of 300 W has been designed and developed with a switching frequency of 20 kHz. Experimental results confirm the effectiveness of the theoretical analysis, the aforementioned advantages, and features of the proposed multiport ZQR DC/DC converter.

• Zaman, Sakhi; Khan, Latif Ullah; Hussain, Irshad & Mihet-Popa, Lucian (2022). Fast Computation of Highly Oscillatory ODE Problems: Applications in High Frequency Communication Circuits. Symmetry. 14(1), s. 1–12. doi: 10.3390/sym14010115. Fulltekst i vitenarkiv Vis sammendrag

  Two types of algorithms are presented to approximate highly oscillatory and non-oscillatory first order ordinary differential equations. In the first approach, radial basis function interpolation is used to approximate the function f(t,x), then quadrature method is used to evaluate the integral part of the equation. The method is implementable to non-oscillatory first order initial value problems. The second approach is more generic and can approximate highly oscillatory and non-oscillatory initial value problems. Accordingly, the first order initial value problem with oscillatory forcing term is transformed into an integral with oscillatory Fourier kernel. The transformed oscillatory integral is then evaluated numerically by the Levin collocation method. Finally, non-linear form of the initial value problems with oscillatory forcing term is converted into a linear form using Bernoulli’s transformation. The resulting linear oscillatory problem is then computed by the new approaches. To justify accuracy of the algorithms, few numerical examples are added from the literature.

• Khan, Suhaib Ahmad; Tariq, Mohd; Khan, Asfar Ali; Alamri, Basem & Mihet-Popa, Lucian (2022). Influence of Area and Volume Effect on Dielectric Behaviour of the Mineral Oil-Based Nanofluids. Energies. 15(9). doi: 10.3390/en15093354. Fulltekst i vitenarkiv Vis sammendrag

  Transformer oil is conventionally used as an insulating liquid for the purpose of insulation and cooling in power transformers. The rise in the power demand has put stress on the existing insulation system used for power transmission. Nanotechnology provides an advanced approach to upgrade the conventional insulation system by producing nano-oil with enhanced dielectric characteristics. The aim of the study is to present the influence of area volume effect on the dielectric performance of mineral oil and its nanofluids. In this paper, nanofluids are prepared by dispersing two different concentrations of SiO2 nanoparticles in base transformer oil using a two-step method. The effect of area and volume is investigated on nanofluids in the laboratory using coaxial electrode configurations under different test conditions. The AC breakdown voltage and maximum electric stress is determined for the pure oil and nanofluids. The results show that the addition of SiO2 nanoparticles significantly improves the dielectric characteristics of transformer oil. Moreover, the breakdown phenomenon is also discussed to analyze the effect of nanoparticle, stressed area, and stressed volume on the dielectric strength of insulating oil. Nanofluids could be an alternative to mineral oil.

• Oliver, Jeba Singh; David, Prince Winston; Balachandran, Praveen Kumar & Mihet-Popa, Lucian (2022). Analysis of Grid-Interactive PV-Fed BLDC Pump Using Optimized MPPT in DC–DC Converters. Sustainability. 14(12). doi: 10.3390/su14127205. Fulltekst i vitenarkiv Vis sammendrag

  In solar photovoltaic (PV) system-based Brushless DC (BLDC) motors for water pumping application, the role of DC/DC converters is very important. In order to extract the maximum power from the PV array, an efficient DC/DC converter is essential at the intermediate stage. In this work, different DC/DC converter topologies suitable for BLDC motors are proposed. The converters are supported by an optimized maximum power point tracking system to provide a reliable operation. Recent optimization algorithms such as fuzzy logic, perturb and observe, grey wolf, and whale optimization are implemented with the PI controller in maximum power point tracking to maximize the conversion efficiency. The obtained results using SEPIC, LUO, and interleaved LUO converters provide a comparative study in the case of converter output, motor parameters, and grid output. The performance analysis on three different converters and multiple optimization methods are carried out. By analyzing the performance of different converter topologies, the interleaved LUO converter outperforms the other two converters with the results of a voltage gain ratio of 1:22, conversion efficiency of 98.3%, and grid current THD of 2.9%. Moreover, regarding the power quality aspect, the total harmonic distortion of the grid current is maintained below the IEEE-519 standard. In addition, the developed system has an advantage of operating both in stand-alone and grid-connected operation modes.

• Venkatesh, Banala; Sankaramurthy, Padmini; Chokkalingam, Bharatiraja & Mihet-Popa, Lucian (2022). Managing the demand in Smart Grid Based on Load shifting with Controllable Devices Using Hybrid WFS2ACSO Technique. Energies. 15(3), s. 1–25. doi: 10.3390/en15030790. Fulltekst i vitenarkiv Vis sammendrag

  The Demand Side Management (DSM) introduced in Smart Grid (SG), which depends on load shifting with huge number of devices is presented in this work. The proposed hybrid strategy is the joint implementation of Wingsuit Flying Search (WFSA) algorithm and Artificial Cell Swarm Optimization (ACSO). The searching behavior of WFSA is enhanced by ACSO. Hence, it is named as WFS2ACSO. This technique aims at minimization of electricity bill, power consumption, and Peak Average Ratio (PAR). The daily load change method presented in this manuscript is utilized for defusing the minimization issues. The present method is performed in SG that constitutes three different types of loads on a residential area, a commercial area, and an industrial area. Simulation results demonstrate that the projected DSM methodology achieves considerable savings, as peak load demand of SG decreases. Further, the variation in PAR levels with and without the DSM methodology is also presented. The proposed model is executed on a MATLAB simulation platform with two case studies based on optimization methods like WFSA, WFS2ACSO). The results obtained present the hybridized algorithm effectiveness as compared with other trendsetting optimization techniques like Ant lion optimization (ALO) and particle swarm optimization (PSO).

• Elavarasan, Rajvikram Madurai Elavarasan; Pugazhendhi, Rishi; Irfan, Muhammad; Mihet-Popa, Lucian; Campana, Pietro Elia & Khan, Irfan Ahmad (2021). A Novel Sustainable Development Goal 7 Composite Index as the Paradigm for Energy Sustainability Assessment: A Case Study from Europe. Applied Energy. ISSN 0306-2619. 307. doi: 10.1016/j.apenergy.2021.118173. Fulltekst i vitenarkiv Vis sammendrag

  The Sustainable Development Goal 7 endeavors to ameliorate the energy system towards sustainability. Moni-toring the country’s progress to the goal will be of utmost for the government to take suitable actions and thus, constructing a performance monitoring index for Sustainable Development Goal 7 would tune the pace of implementation. This study aims to develop a novel Sustainable Development Goal 7 or Energy Sustainability Composite Index to assess the energy sustainability performance. Since Europe tends to have diverged efforts towards energy sustainability, assessing them with the proposed Sustainable Development Goal 7 composite index would provide the evidence needed for effective sustainable development strategies. By describing Europe, the authors signify 40 European countries and the selection of country depends on the availability of all the data that are required for the energy sustainability assessment. In this study, the analyzed energy sustainability as-pects include clean energy conversion, energy security, energy accessibility, energy intensity and carbon in-tensity. The results show that Iceland, Norway, and Sweden tops in energy sustainability aspects with scores of 0.7313, 0.6967, and 0.6313 (on a scale of 0 to 1), respectively. The proposed Sustainable Development Goal 7 composite index is also compared with the actual Sustainable Development Goal 7 index, which comprises the indicators defined by the United Nations. The prime difference between the proposed Sustainable Development Goal 7 composite index and the actual Sustainable Development Goal 7 index resides in the consideration of energy security and carbon intensity indicators and in the framework designed to evaluate the clean energy prevalence. The evaluated actual Sustainable Development Goal 7 index scores of Germany and France are 0.4915 and 0.4656, respectively. On comparing with the proposed Sustainable Development Goal 7 composite index scores, the scores decreased by 20.9% for Germany and increased by 7.2% for France. The robustness of the proposed composite index relies on reducing the effect of outliers by using a modified min–max methodology, namely Aggregated Normalization based on Maximum and Minimum Outliers for normalization and the subsequent weightage allocation criteria utilized in Analytic Hierarchy Process methodology. Sensitivity analyses high-lighted that the clean energy indicator is the most influencing indicator for the designed composite index. Nevertheless, uncertainty analysis indicates that the weightage scenario has a more prominent influence than various normalization and aggregation methods

• Madasamy, P.; Verma, Rajesh; Bharatiraja, C.; Barnabas, Paul Glady J; Srihari, T. & Munda, Josiah Lange [Vis alle 7 forfattere av denne artikkelen] (2021). Hybrid Multicarrier Random Space Vector PWM for the Mitigation the Acoustic Noise. Electronics (Basel). 10(12). doi: 10.3390/electronics10121483. Fulltekst i vitenarkiv Vis sammendrag

  The pulse width modulation (PWM) inverter is obvious for any industrial and power sector application. Particularly industrial drives are very keen on the industrial standards. Many modulations approached such a drives objects of DC-link consumption, harmonics suppression in lower and higher order spectrum and noise reduction. The still random PWM is a best candidate for reducing the noises on the PWM operated AC drives. There are various Random PWM (RPWM) methods has been developed and investigated for the PWM inverter fed drive noise reductions, still the shortcomings are existence on these method items of their less randomness and complex digital circuitry. These PWM dealt the spreading harmonics there by decreasing harmonic effects on the system. However, these techniques overlook the effect of acoustic noise and DC -link utilizations Therefore, in this paper mainly deals with to combined RPWM principle in space vector PWM (SVPWM) to generate random PWM generation using asymmetric frequency multi carrier called multicarrier random space vector PWM (MCRSVPWM). The SVM agreements with multicarrier (different fixed frequencies as carrier waves) which are chosen with the aid of a random binary bit generator. The proposed RSVM generated pulses with a randomized triangular carrier (4 ± 1.5 kHz), while the conventional RPWM method contains of the random pulse position with a fixed frequency triangular carrier. The simulation study is performed through MATLAB/Simulink for 3 HP asynchronous induction motor drive. The Experimental validation of proposed MCRSVPWM is tested with 2kW six switch (Power MOSFET – SCH2080KE) inverter power module fed induction motor drive.

• Ali, Ahmad; Rahman, Kashif Syed Abdul; Ali, Nasir; Akhtar, Rasool; Sheroze, Liaquat & Padmanaban, Sanjeevikumar [Vis alle 7 forfattere av denne artikkelen] (2021). Controller Parameters Optimization for Multi-Terminal DC Power System Using Ant Colony Optimization. IEEE Access. 9, s. 59910–59919. doi: 10.1109/ACCESS.2021.3073491. Fulltekst i vitenarkiv Vis sammendrag

  Voltage source converter based multi – terminal DC grids (VSC – MTDC) are widely used for integration of renewable resources. Control of these grids requires vector control method, which includes inner and outer current controllers, tuning of these controllers is very important. Conventionally used tuning methods consider approximated linear model to tune the proportional – integral (PI) parameters of voltage source converter (VSC) which fails to produce optimum disturbance rejection results. In this research an Ant Colony Optimization (ACO) technique is used to get the optimum parameters of inner and outer power control layers for multi – terminal DC system. ACO is applied simultaneously on inner and outer control layers and results are compared with classical tuning method. In this paper, a four terminal VSC – MTDC has been used under different sequence of events of disturbances e.g. load change on AC side, active power reference change for inverter and rectifier mode and disconnection of one terminal to evaluate the robustness of ACO algorithm with respect to classical method. The proposed tuning method gives superior results under different disturbance compared to conventional method.

• Das, Soumya Ranjan; Ray, Prakash K.; Sahoo, Arun Kumar; Ramasubbareddy, Somula; Babu, Thanikanti Sudhakar & Nallapaneni, Manoj Kumar [Vis alle 8 forfattere av denne artikkelen] (2021). A Comprehensive Survey on Different Control Strategies and Applications of Active Power Filters for Power Quality Improvement. Energies. 14(15). doi: 10.3390/en14154589. Fulltekst i vitenarkiv Vis sammendrag

  Power quality (PQ) has become an important topic in today’s power system scenario. PQ issues are raised not only in normal three-phase systems but also with the incorporation of different distributed generations (DGs), including renewable energy sources, storage systems, and other systems like diesel generators, fuel cells, etc. The prevalence of these issues comes from the non-linear features and rapid changing of power electronics devices, such as switch-mode converters for adjustable speed drives and diode or thyristor rectifiers. The wide use of these fast switching devices in the utility system leads to an increase in disturbances associated with harmonics and reactive power. The occurrence of PQ disturbances in turn creates several unwanted effects on the utility system. Therefore, many researchers are working on the enhancement of PQ using different custom power devices (CPDs). In this work, the authors highlight the significance of the PQ in the utility network, its effect, and its solution, using different CPDs, such as passive, active, and hybrid filters. Further, the authors point out several compensation strategies, including reference signal generation and gating signal strategies. In addition, this paper also presents the role of the active power filter (APF) in different DG systems. Some technical and economic considerations and future developments are also discussed in this literature. For easy reference, a volume of journals of more than 140 publications on this particular subject is reported. The effectiveness of this research work will boost researchers’ ability to select proper control methodology and compensation strategy for various applications of APFs for improving PQ.

• Ali, Muhammad; Hafeez, Ghulam; Farooq, Ajmal; Shafiq, Zeeshan; Faheem, Ali & Usman, Muhammad [Vis alle 7 forfattere av denne artikkelen] (2021). A Novel Control Approach to Hybrid Multilevel Inverter for High Power Applications. Energies. 14(15). doi: 10.3390/en14154563. Fulltekst i vitenarkiv Vis sammendrag

  This paper proposes a hybrid control scheme for a newly devised hybrid multilevel inverter (HMLI) topology. The circuit configuration of HMLI is comprised of a cascaded converter module (CCM), connected in series with an H-bridge converter. Initially, a finite set model predictive control (FS-MPC) is adopted as a control scheme, and theoretical analysis is carried out in MATLAB/Simulink. Later, in the real-time implementation of the HMLI topology, a hybrid control scheme which is a variant of the FS-MPC method has been proposed. The proposed control method is computationally efficient and therefore has been employed to the HMLI topology to mitigate the high-frequency switching limitation of the conventional MPC. Moreover, a comparative analysis is carried to illustrate the advantages of the proposed work that includes low switching losses, higher efficiency, and improved total harmonic distortion (THD) in output current. The inverter topology and stability of the proposed control method have been validated through simulation results in MATLAB/Simulink environment. Experimental results via low-voltage laboratory prototype have been added and compared to realize the study in practice.

• Mahesh, Aganti; Bharatiraja, Chokkalingam & Mihet-Popa, Lucian (2021). Inductive Wireless Power Transfer Charging for Electric Vehicles–A Review. IEEE Access. 9, s. 13667–137713. doi: 10.1109/ACCESS.2021.3116678. Fulltekst i vitenarkiv Vis sammendrag

  Considering a future scenario in which a driverless Electric Vehicle (EV) needs an automatic charging system without human intervention. In this regard, there is a requirement for a fully automatable, fast, safe, cost-effective, and reliable charging infrastructure that provides a profitable business model and fast adoption in the electrified transportation systems. These qualities can be comprehended through wireless charging systems. Wireless Power Transfer (WPT) is a futuristic technology with the advantage of flexibility, convenience, safety, and the capability of becoming fully automated. In WPT methods resonant inductive wireless charging has to gain more attention compared to other wireless power transfer methods due to high efficiency and easy maintenance. This literature presents a review of the status of Resonant Inductive Wireless Power Transfer Charging technology also highlighting the present status and its future of the wireless EV market. First, the paper delivers a brief history throw lights on wireless charging methods, highlighting the pros and cons. Then, the paper aids a comparative review of different type’s inductive pads, rails, and compensations technologies done so far. The static and dynamic charging techniques and their characteristics are also illustrated. The role and importance of power electronics and converter types used in various applications are discussed. The batteries and their management systems as well as various problems involved in WPT are also addressed. Different trades like cyber security economic effects, health and safety, foreign object detection, and the effect and impact on the distribution grid are explored. Prospects and challenges involved in wireless charging systems are also highlighting in this work. We believe that this work could help further the research and development of WPT systems.

• Tamilarasu, Karthick; Sathiasamuel, Charles Raja; Josep, Jeslin Drusila Nesamalar; Elavarasan, Rajvikram Madurai & Mihet-Popa, Lucian (2021). Reinforced Demand Side Management for Educational Institution with incorporation of User’s Comfort. Energies. 14(10). doi: 10.3390/en14102855. Fulltekst i vitenarkiv Vis sammendrag

  Soaring energy demand and the establishment of various trends in the energy market have paved the way for developing demand-side management (DSM) from the consumer side. This paper proposes a reinforced DSM (RDSM) approach that uses an enhanced binary gray wolf optimization algorithm (EBGWO) that benefits the consumer premises with load scheduling, and peak demand reduction. To date, DSM research has been carried out for residential, commercial and industrial loads, whereas DSM approaches for educational loads have been less studied. The institution load also consumes much utility energy during peak hours, making institutional consumers pay a high amount of cost for energy consumption during peak hours. The proposed objective is to reduce the total electricity cost and to improve the operating efficiency of the entire load profile at an educational institution. The proposed architecture integrates the solar PV (SPV) generation that supplies the user-comfort loads during peak operating hours. User comfort is determined with a metric termed the user comfort index (UCI). The novelty of the proposed work is highlighted by modeling a separate class of loads for temperature-controlled air conditioners (AC), supplying the user comfort loads from SPV generation and determining user comfort with percentage UCI. The improved transfer function used in the proposed EBGWO algorithm performs faster in optimizing nonlinear objective problems. The electricity price in the peak hours is high compared to the offpeak hours. The proposed EBGWO algorithm shift and schedules the loads from the peak hours to off-peak hours, and incorporating SPV in satisfying the user comfort loads aids in reducing the power consumption from the utility during peak hours. Thus, the proposed EBGWO algorithm greatly helps the consumer side decrease the peak-to-average ratio (PAR), improve user comfort significantly, reduce the peak demand, and save the institution’s electricity cost by USD 653.046.

• Lütge, Christopher; Poszler, Franziska; Acosta, Aida Joaquin; Danks, David; Gottehrer, Gail & Mihet-Popa, Lucian [Vis alle 7 forfattere av denne artikkelen] (2021). AI4People: Ethical Guidelines for the Automotive Sector – Fundamental Requirements and Practical Recommendations. International Journal of Technoethics (IJT). ISSN 1947-3451. 12(1), s. 101–125. doi: 10.4018/IJT.20210101.oa2. Fulltekst i vitenarkiv Vis sammendrag

  This paper presents the work of the AI4People-Automotive Committee established to advise more concretely on specific ethical issues that arise from autonomous vehicles (AVs). Practical recommendations for the automotive sector are provided across the topic areas: human agency and oversight, technical robustness and safety, privacy and data governance, transparency, diversity, non-discrimination and fairness, societal and environmental wellbeing, as well as accountability. By doing so, this paper distinguishes between policy recommendations that aim to assist policymakers in setting acceptable standards and industry recommendations that formulate guidelines for companies across their value chain. In the future, the automotive sector may rely on these recommendations to determine relevant next steps and to ensure that AVs comply with ethical principles.

• Asif, Mohd; Tariq, Mohd; Sarwar, Adil; Hussan, Md. Reyaz; Ahmad, Shafiq F. & Mihet-Popa, Lucian [Vis alle 7 forfattere av denne artikkelen] (2021). A robust multilevel inverter topology for operation under fault conditions. Electronics (Basel). 10(24), s. 1–18. doi: 10.3390/electronics10243099. Fulltekst i vitenarkiv Vis sammendrag

  Multilevel inverters (MLIs) are new demanding topologies that have low total harmonic distortion (THD) and low voltage stress across the switches make them ideal for medium and high-power applications. The authenticity of semiconductor devices is one of the main concerns for these MLIs to operate properly. With an increment in the number of switches in multilevel inverters, the pos-sibility of the fault also arises. Hence, a reliable 5- level inverter topology with fault-tolerant ability has been proposed. The proposed topology can withstand against of Open Circuit (OC) fault caused when any single switch fails. The proposed configuration is fault-tolerant and reliable as compared to the conventional multilevel inverters. Simulation of the proposed topology is done in MATLAB-Simulink and PLECS software packages, and the results obtained for normal (pre-fault), during the fault, and post-fault conditions are discussed. Experimental results also prove the proposed cell topology's robustness and effectiveness in tolerating OC faults across the switches. Furthermore, a thorough comparison is provided to demonstrate the superiority of the proposed topology in comparison to recently published topologies that have fault-tolerant features

• Rengasamy, Mageswaran; Gangatharan, Sivasankar; Elavarasan, Rajvikram Madurai & Mihet-Popa, Lucian (2021). Incorporation of Microgrid Technology Solutions to Reduce Power Loss in a Distribution Network with Elimination of Inefficient Power Conversion Strategies. Sustainability. 13(24). doi: 10.3390/su132413882. Fulltekst i vitenarkiv Vis sammendrag

  The increase in energy-efficient DC appliances and electronic gadgets has led to an upheaval in the usage of AC–DC power convertors; hence, power loss in converter devices is cumulatively increasing. Evolving microgrid technology has also become deeply integrated with the conversion process due to increased power converters in its infrastructure, significantly worsening the power loss situation. One of the practical solutions to this disturbance is to reduce conversion losses in domestic distribution systems through the optimal deployment of the battery storage system and solar PV power using microgrid technology. In this paper, a novel energy management system is developed that uses a new control algorithm, termed Inefficient Power Conversion Elimination Algorithm (IPCEA). The proposed algorithm compares the Net Transferable Power (NTP) available on the DC side with the loss rate across the converter. The converter is switched off (or disconnected from the grid and load) if the NTP is less than 20% of the converter rating to avoid low-efficiency power conversion. The solar PV system is connected to the DC bus to supply the DC loads while the AC loads are supplied from the AC source (utility power). An auxiliary battery pack is integrated to the DC side to feed DC loads during the absence of solar energy. A battery energy storage system (BESS) is deployed to manage energy distribution effectively. The power distribution is managed using a centralized microgrid controller, and the load demand is met accordingly. Thereby, the power generated by the solar PV can be utilized effectively. Microgrid technology’s effectiveness is emphasized by comparative analysis, and the achievements are discussed in detail and highlighted using a prototype model.

• Islam, Md. Ariful; Singh, Jai Govind; Jahan, Israt; Lipu, M.S. Hossain; Jamal, Taskin & Elavarasan, Rajvikram Madurai [Vis alle 7 forfattere av denne artikkelen] (2021). Modelling and Performance Evaluation of ANFIS Controller-Based Bidirectional Power Management Scheme in Plug-in Electric Vehicles Integrated with Electric Grid. IEEE Access. 9, s. 166762–166780. doi: 10.1109/ACCESS.2021.3135190. Fulltekst i vitenarkiv Vis sammendrag

  A bi-directional power exchange between the plug-in electric vehicle (PEV) and the AC electrical grid is necessary to perform the Vehicle to Grid (V2G) and Grid to Vehicle (G2V) operations. While performing these operations, different power converters and controllers play an important role as mediators between the PEV and electric grid. Various works have demonstrated the utilization of controllers for PEV’s battery power management. However, the existing conventional controllers have technical shortcomings about vulnerability to controller gain, accurate mathematical modelling, poor adaptability, sluggish response to a sudden outburst and lengthy interval execution processing. Therefore, this paper develops an adaptive neuro-fuzzy inference system (ANFIS) control strategy based bidirectional power management scheme to ensure the optimal electrical power flow exchange between the AC electrical grid and battery storage system in PEVs. This paper aims to reduce the stress on the grid power side and utilize the unused power properly. The performance of the ANFIS model is varied using two PEVs based on real-life power consumptions by different loads at home based on five operational modes. Besides, a comparative analysis between the ANFIS controller and the PI controller is carried out to demonstrate the effectiveness of the proposed control scheme. The results illustrate that the proposed ANFIS controller delivers a smoother power injection from the PEV to the AC power grid with the least harmonics as well as achieves a smoother battery profile and less distortion when power is absorbed by PEV battery.

• Madasamy, P.; Verma, Rajesh; Rameshbabu, A; Murugesan, A; Umamageswari, R & Munda, Josiah Lange [Vis alle 8 forfattere av denne artikkelen] (2021). Neutral Point Clamped Transformerless Multilevel Converter for Grid-Connected Photovoltaic System. Electronics (Basel). 10(8). doi: 10.3390/electronics10080977. Fulltekst i vitenarkiv Vis sammendrag

  Transformer-less (TL) inverter topologies have elicited further special treatment in photo-voltaic (PV) power system as they provide high efficiency and low cost. Neutral point clamped (NPC) multilevel-inverter (MLI) topologies-based transformer-less are being immensely used in grid-connected medium-voltage high-power claims. Unfortunately, these topologies such as NPC-MLI, full-bridge inverter with DC bypass (FB-DCBP) suffer from the shoot-through problem on the bridge legs, which affect the reliability of the implementation. Based on the previous above credits, a T type neutral point clamped (TNP) - MLI (TNP-MLI) with Transformer-less topology called TL-TNP-MLI is presented to be an alternate which can be suitable in the grid connected PV power generation systems. The suggested TL-TNP-MLI topologies free from inverter bridge legs shoot-through burden, switching frequency common-mode current (CMC), and leakage current. The control system of the grid interface with hysteresis current control (HCC) strategy is proposed. The effectiveness of the proposed PV connected transformer-less TNP-MLI topology with different grid and PV scenario has been verified through the MATLAB/Simulink simulation model and field-programmable gate area (FPGA) based experimental results for a 1.5 kW system.

• Kamalesh, M.S.; Senthilnathan, Nattuthurai; Bharatiraja, Chokkalingam & Mihet-Popa, Lucian (2021). Mitigation of Circulating Current With Effective Energy Management In Low Power PV-FC-Battery-Microgrid. International Transactions on Electrical Energy Systems. 31(6). doi: 10.1002/2050-7038.12899. Fulltekst i vitenarkiv
• Zouinkhi, Ahmed; Flah, Aymen & Mihet-Popa, Lucian (2021). A Novel Energy-Safe Algorithm for Enhancing the Battery Life for IoT Sensors’ Applications. Energies. 14(20). doi: 10.3390/en14206613. Fulltekst i vitenarkiv Vis sammendrag

  Energy safe is mandatory for all isolated IoT tools, as in long way roads, mountains, or even in smart cities. If increasing the lifetime of these tools, the rentability of the global network loop becomes more efficient. Therefore, this paper's base main is to present a new approach for saving energy inside the source nods by supervising the state of energy inside each source nod and calculating the duty cycle factor. The relationship between these parameters is based on an optimization problem formulation. In this respect, the present paper is designed to propose a new approach that deals with increasing the lifetime of the Wireless Sensors Network (WSN) attached nodes, as fixed in the application. The newly devised design rests on implementing the IEEE 802.15.4 standard beacon-enabled mode, involving a cluster tree topology. Accordingly, every subgroup is allotted to apply a specifically different duty cycle, depending on the battery's remaining energy level, which contributes to creating a wide range of functional modes. Hence, various thresholds are defined. Simulation results are proving the efficiency of the proposed approach and show the energetic benefit. The proposed flowchart has minimized the consumed energy for the WSN, which improve the battery lifetime and enhance the IoT applications robustness. Simulations and experiments have been carried out under different conditions and the results proved that the proposed method is a viable solution.

• Biswal, Saubhagya; Shankar, Gauri; Elavarasan, Rajvikram Madurai & Mihet-Popa, Lucian (2021). Optimal Allocation/Sizing of DGs/Capacitors in Reconfigured Radial Distribution System using Quasi-Reflected Slime Mould Algorithm. IEEE Access. 9, s. 125658–125677. doi: 10.1109/ACCESS.2021.3111027. Fulltekst i vitenarkiv Vis sammendrag

  Increased load demands worsen distribution system problems such as greater line losses, voltage deviation and a plethora of other concerns. This current work presents an approach stressing simultaneous optimal allocation and sizing of capacitor banks and distributed generations, as well as optimal radial distribution system (RDS) reconfiguration, to address these difficulties. The above objectives are accomplished through the maiden application of the proposed quasi-reflection-based slime mould algorithm (QRSMA). The efficacy of QRSMA is established by testing it on different benchmark functions. A new modified backward forward load flow approach is also proposed and validated by comparing its results to those obtained using MATPOWER software for IEEE 69, 85, and 118 bus RDSs. The proposed load flow technique is independent of the sequential bus numbering scheme and may be applied to any RDS network topology. The proposed QRSMA is tested on 118 bus RDS and to prove its effectiveness; its results are compared to those of other studied algorithms. The study takes into account both fixed and variable loading scenarios. A cost-benefit analysis of the strategy is also performed in order to make the methodology more realistic.

• Abraham, Dominic Savio; Verma, Rajesh; Lakshmikhandan, Kanagaraj; Thulasi, Sundar Rajan Giri; Narayanamoorthi, Rajamanickam & Chokkalingam, Bharatiraja [Vis alle 8 forfattere av denne artikkelen] (2021). Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids. Electronics (Basel). 10(16). doi: 10.3390/electronics10161895. Fulltekst i vitenarkiv Vis sammendrag

  The usage of electric vehicles (EV) has been increasing over the last few years due to a rise in fossil fuel prices and the rate of increasing carbon dioxide (CO2) emissions. EV-charging stations are powered by existing utility power grid systems, increasing the stress on the utility grid and the load demand at the distribution side. DC grid-based EV charging is more efficient than AC distribution because of its higher reliability, power conversion efficiency, simple interfacing with renewable energy sources (RESs), and integration of energy storage units (ESU). RES-generated power storage in local ESU is an alternative solution for managing the utility grid demand. In addition, to maintain the EV charging demand at the microgrid levels, energy management and control strategies must carefully power the EV battery charging unit. In addition, charging stations require dedicated converter topologies, control strategies, and need to follow set levels and standards. Based on EV, ESU, and RES accessibility, different types of microgrid architecture and control strategies are used to ensure optimum operation at the EV-charging point. Based on the above said merits, this review paper presents different RES-connected architecture and control strategies used in EV-charging stations. It highlights the importance of different charging station architectures with current power converter topologies proposed in the literature. In addition, a comparison of microgrid-based charging station architecture with its energy management, control strategies, and charging converter controls are also presented. The different levels and types of charging stations used for EV charging, in addition to controls and connectors used, are also discussed. An experiment-based energy management strategy was developed to control power flow among the available sources and charging terminals for the effective utilization of generated renewable power. The main motive of the EMS and its control is to maximize the usage of RES consumption. This review also provides the challenges and opportunities in EV-charging, and parameters in selecting appropriate charging stations.

• Yohanandhan, Rajaa Vikhram; Elavarasan, Rajvikram Madurai; Pugazhendhi, Rishi; Premkumar, Manoharan; Mihet-Popa, Lucian & Terzija, Vladimir (2021). A holistic review on Cyber-Physical Power System (CPPS) testbeds for secure and sustainable electric power grid – Part – II: Classification, overview and assessment of CPPS testbeds. International Journal of Electrical Power & Energy Systems. ISSN 0142-0615. 137. doi: 10.1016/j.ijepes.2021.107721. Fulltekst i vitenarkiv
• Yohanandhan, Rajaa Vikhram; Elavarasan, Rajvikram Madurai; Pugazhendhi, Rishi; Premkumar, Manoharan; Mihet-Popa, Lucian & Terzija, Vladimir (2021). A Holistic Review on Cyber-Physical Power System (CPPS) Testbeds for Secure and Sustainable Electric Power Grid – Part – I: Background on CPPS and Necessity of CPPS Testbeds. International Journal of Electrical Power & Energy Systems. ISSN 0142-0615. 136. doi: 10.1016/j.ijepes.2021.107718. Fulltekst i vitenarkiv Vis sammendrag

  The integration of advanced Information and Communication Technologies (ICTs) in the conventional electric power grid is evolving into a Cyber-Physical Power System (CPPS). The seamless integration of control, communication, and computing operations allow CPPS to be fully monitored and controlled. Threats, vulnerabilities, and catastrophic attacks will intrude as CPPS monitoring, protection, and control functions advance. For the CPPS to operate safely, securely, and efficiently, sustainable cybersecurity solutions must be developed, and the power grid's reliability and resilience must be maintained even when exposed to unfavorable network conditions. While more distributed and renewable energy sources are connected to the grid, cybersecurity helps to ensure the supply of electricity is sustainable and of high quality. The validation of such sustainable cybersecurity analysis goes beyond the traditional power grid network analysis, which means that the test should integrate the physical and cyber system behavior and respond to the network attacks. To analyze the cybersecurity and cyberattacks in the practical CPPS, comprehensive and realistic CPPS testbeds are needed. The heterogeneous nature of the CPPS concept urges multidisciplinary testbeds with various functions and capabilities to evaluate the new cyber-attacks, vulnerabilities, and threats in CPPS. Using this CPPS testbed framework, the different types of cyber-attack can be detected, and detection algorithm can be evaluated, and helps to enhance the development of sustainable cybersecurity defenses for realistic CPPS environment with the increasingly dense integration of distributed energy resources (DERs). This Part-I paper review the CPPS testbeds in the view of the physical power system layer, sensing layer, communication layer, control layer, application layer, test platforms, and research goals with the fusion of cyber and physical systems. In addition, this review presented an overview, structure, and application-based evaluation of existing testbeds from the industry and institutions. The various research areas in CPPS are reviewed first to show the research trends on different aspects of CPPS which have gained significant attention in the past decade. The necessity of testbeds for cyberattacks and sustainable cybersecurity analysis in CPPS are then described. Finally, the NIST framework for CPS, CPPS domains, and research areas are presented. Further the Part-II paper will review the classification, overview, and assessment of CPPS testbeds.

• Yohanandhan, Rajaa Vikhram; Elavarasan, Rajvikram Madurai; Pugazhendhi, Rishi; Manoharannd, Premkumar; Mihet-Popa, Lucian & Zhao, Zumbo [Vis alle 7 forfattere av denne artikkelen] (2021). A Specialized Review On Outlook of Future Cyber-Physical Power System (CPPS) testbeds for securing electric power grid. International Journal of Electrical Power & Energy Systems. ISSN 0142-0615. 136. doi: 10.1016/j.ijepes.2021.107720. Fulltekst i vitenarkiv Vis sammendrag

  The Cyber-Physical Power System (CPPS) is a new type of system in which the traditional energy system is integrated into the information network with control systems, communication networks, and computational units. CPPS is the foundation of a long-term transformation of energy management that will fundamentally alter the perspective and application pattern of traditional energy research. The strong interactions between systems in a CPPS introduce new challenges in maintaining high supply security, as new factors can affect the overall security of the power system. Such factors include cybersecurity, the behaviour and constraints of neighbouring energy systems, and the dynamics of interactions between the various systems. Integrating computing, com-munications, and control at all levels of electrical energy generation, transmission, distribution, utilisation, and storage in CPPS increases vulnerabilities and complicates security. Security studies must reflect the character-istics of the CPPS infrastructure in actual testing environments that support the interfacing of real-world hard-ware devices. CPPS testbeds are effective in this context because they provide testing capabilities for evaluating the synergistic relationship between physical and virtual components in controlled environments. Security- oriented CPPS testbeds are invaluable for performing cybersecurity and cyberattack analyses, identifying sys-tem threats and vulnerabilities in various layers of CPPS, implementing intrusion detection and prevention al-gorithms, and evaluating the efficacy of mitigation techniques without imposing excessive economic burdens or posing safety risks. This paper provides a comprehensive review of CPPS testbeds from the standpoint of the physical power system layer, cyber system layer, and cyber-physical fusion layer. Following a brief description of the importance of testbeds for cybersecurity research in CPPS, and a brief classification of existing CPPS testbeds for cyberattacks, and cybersecurity analysis in CPPS is presented. A detailed overview of the outlook for future CPPS testbeds in terms of communication, control, computing, and educational perspective is provided. Finally, the work is concluded with future research directions for developing a secure electric power grid.

• Chakraborty, Suprava; Verma, Sumit; Salgotra, Aprajita; Elavarasan, Rajvikram Madurai Elavarasan; Elangovan, Devaraj & Mihet-Popa, Lucian (2021). Solar-Based DG Allocation Using Harris Hawks Optimization While Considering Practical Aspects. Energies. 14(16). doi: 10.3390/en14165206. Fulltekst i vitenarkiv Vis sammendrag

  The restructuring of power systems and the ever-increasing demand for electricity have given rise to congestion in power networks. The use of distributed generators (DGs) may play a significant role in tackling such issues. DGs may be integrated with electrical power networks to regulate the drift of power in the transmission lines, thereby increasing the power transfer capabilities of lines and improving the overall performance of electrical networks. In this article, an effective method based on the Harris hawks optimization (HHO) algorithm is used to select the optimum capacity, number, and site of solar-based DGs to reduce real power losses and voltage deviation. The proposed HHO has been tested with a complex benchmark function then applied to the IEEE 33 and IEEE 69 bus radial distribution systems. The single and multiple solar-based DGs are optimized for the optimum size and site with a unity power factor. It is observed that the overall performance of the systems is enhanced when additional DGs are installed. Moreover, considering the stochastic and sporadic nature of solar irradiance, the practical size of DG has been suggested based on analysis that may be adopted while designing the actual photovoltaic (PV) plant for usage. The obtained simulation outcomes are compared with the latest state-of-the-art literature and suggest that the proposed HHO is capable of processing complex high dimensional benchmark functions and has capability to handle problems pertaining to electrical distribution in an effective manner.

• CHITTOOR, PRITHVI KRISHNA; Chokkalingam, Bharatiraja & Mihet-Popa, Lucian (2021). A Review on UAV Wireless Charging: Fundamentals, Applications, Charging Techniques and Standards. IEEE Access. 9. doi: 10.1109/ACCESS.2021.3077041. Fulltekst i vitenarkiv Vis sammendrag

  Unmanned Aerial Vehicles (UAVs) are becoming increasingly popular for applications such as inspections, delivery, agriculture, surveillance, and many more. It is estimated that, by 2040, UAVs/drones will become a mainstream delivery channel to satisfy the growing demand for parcel delivery. Though the UAVs are gaining interest in civil applications, the future of UAV charging is facing a set of vital concerns and open research challenges. Considering the case of parcel delivery, handling countless drones and their charging will become complex and laborious. The need for non-contact based multi-device charging techniques will be crucial in saving time and human resources. To efficiently address this issue, Wireless Power Transmission (WPT) for UAVs is a promising technology for multi-drone charging and autonomous handling of multiple devices. In the literature of the past five years, limited surveys were conducted for wireless UAV charging. Moreover, vital problems such as coil weight constraints, comparison between existing charging techniques, shielding methods and many other key issues are not addressed. This motivates the author in conducting this review for addressing the crucial aspects of wireless UAV charging. Furthermore, this review provides a comprehensive comparative study on wireless charging's technical aspects conducted by prominent research laboratories, universities, and industries. The paper also discusses UAVs' history, UAVs structure, categories of UAVs, mathematical formulation of coil and WPT standards for safer operation.

• Subramanian, Senthilkumar; Chandramohan, Sankaralingam; Elavarasan, Rajvikram Madurai; Vijayaraghav, Raghavendra Rajan; Raju, Kannadasan & Mihet-Popa, Lucian (2021). An Evaluation on Wind Energy Potential using Multi-Objective Optimization-based Non-dominated Sorting Genetic Algorithm III. Sustainability. 13(1). doi: 10.3390/su13010410. Fulltekst i vitenarkiv Vis sammendrag

  Wind energy is an abundant renewable energy resource that is extensively used worldwide in recent years. The present work proposes a new Multi-Objective Optimization (MOO) based genetic algorithm (GA) model for a wind energy system. The proposed algorithm consists of non-dominated sorting which focuses to maximize the power extraction of the wind turbine and the lifetime of the battery. Also, the performance characteristics of the wind turbine and battery energy storage system (BESS) are analyzed specifically torque, current, voltage, state of charge (SOC), and internal resistance. The complete analysis is carried out in the MATLAB/Simulink platform. The simulated results are compared with existing optimization techniques such as single-objective, multi-objective, and non-dominating sorting GA II (Genetic Algorithm-II). From the observed results, the NSGA III optimization algorithm offers superior performance notably higher turbine power output with higher torque rate, lower speed variation, and lesser degradation rate of the battery. This result attested to the fact that the proposed optimization tool can extract a higher rate of power from a self-excited induction generator (SEIG) when compared with a conventional optimization tool.

• Srivastava, A.K.; Pandey, Ajay Shekhar; Elavarasan, Rajvikram Madurai; Subramaniam, Umashankar; Mekhilef, Saad & Mihet-Popa, Lucian (2021). A Novel Hybrid Feature Selection Method for Day-Ahead Electricity Price Forecasting. Energies. 14(24). doi: 10.3390/en14248455. Fulltekst i vitenarkiv Vis sammendrag

  The paper proposes a novel hybrid feature selection (FS) method for day-ahead electricity price forecasting. The work presents a novel hybrid FS algorithm for obtaining optimal feature set to gain optimal forecast accuracy. The performance of the proposed forecaster is compared with forecasters based on classification tree and regression tree. A hybrid FS method based on the elitist genetic algorithm (GA) and a tree-based method is applied for FS. Making use of selected features, aperformance test of the forecaster was carried out to establish the usefulness of the proposed approach. By way of analyzing and forecasts for day-ahead electricity prices in the Australian electricity markets, the proposed approach is evaluated and it has been established that, with the selected feature, the proposed forecaster consistently outperforms the forecaster with a larger feature set. The proposed method is simulated in MATLAB and WEKA software.

• Madasamy, Periyanayagam; Suresh, Kumar; Bharatiraja, Chokkalingam; Sanjeevikumar, Padmanaban; Mihet-Popa, Lucian & Yusuff, Adedayo (2020). A Modified High Voltage Gain Quasi-Impedance Source Coupled Inductor Multilevel Inverter for Photovoltaic Application. Energies. 13(4). doi: 10.3390/en13040874. Fulltekst i vitenarkiv
• Elavarasan, Rajvikram Madurai; Shafiullah, G.M.; Padmanaban, Sanjeevikumar; Kumar, Nallapaneni Manoj; Annam, Annapurna & Vetrichelvan, Ajayragavan Manavalanagar [Vis alle 8 forfattere av denne artikkelen] (2020). A Comprehensive Review on Renewable Energy Development, Challenges and Policies of leading Indian States with an International Perspective. IEEE Access. 8(1), s. 74432–74457. doi: 10.1109/ACCESS.2020.2988011. Fulltekst i vitenarkiv Vis sammendrag

  Clean and environment-friendly energy harvesting are of prime interest today as it is one of the key enablers in achieving the Sustainable Development Goals (SDGs) as well as accelerates social progress and enhances living standards. India, the second-most populous nation with a population of 1.353 billion, is one of the largest consumers of fossil fuels in the world which is responsible for global warming. An ever-increasing population is projected until 2050, and consequently, the energy demand in the upcoming decades will be co-accelerated by the rapid industrial growth. The Ministry of New and Renewable Energy (MNRE) with the support of National Institution for Transforming India (NITI) Aayog is working to achieve the Indian Government's target of attaining 175 GW through renewable energy resources. Many Indian states are currently increasing their renewable energy capacity in an objective to meet future energy demand. The review paper discusses in-depth about the three Indian states, namely Karnataka, Gujarat, Tamil Nadu, which pioneers the renewable energy production in India. The global energy scenario was discussed in detail with Indian contrast. Further, the barriers to the development of renewable energy generation and policies of the Indian government are discussed in detail to promote renewable energy generation throughout India as well as globally since the challenges are similar for other nations. This study analyzed various prospects of the country in renewable energy which has been done in a purpose to help the scholars, researchers, and policymakers of the nation, as it gives an insight into the present renewable energy scenario of the country.

• Bana, Prabhat Ranjan; Panda, Kaibalya Prasad; Padmanaban, Sanjeevikumar; Mihet-Popa, Lucian; Panda, Gayadhar & Wu, Jianzhong (2020). Closed-Loop Control and Performance Evaluation of Reduced Part Count Multilevel Inverter Interfacing Grid-Connected PV System. IEEE Access. 8, s. 75691–75701. doi: 10.1109/ACCESS.2020.2987620. Fulltekst i vitenarkiv Vis sammendrag

  Multilevel inverters (MLIs) have drawn a tremendous attention in power sector. Application of MLI has grown extensively to improve the power quality and efficiency of the photovoltaic (PV) system. For an MLI interfacing PV system, the size, cost and voltage stress are the key constraints of the MLI that need to be minimized. This paper presents a novel reduced part count MLI interfacing single-stage grid-tied PV system along with a closed-loop control strategy. The proposed MLI consists of n repeating units and a level boosting circuit (LBC) that assists to generate 4n+7 voltage levels instead of 2n+3 levels. Three different algorithms are proposed for suitable selection of dc-link voltages to further enhance the levels. Comparative analysis is carried out to confirm the superiority of developed MLI. The workability of the proposed MLI is investigated with a 1.3 kW PV system. The closed-loop control strategy ensures the maximum power tracking, dc-link voltage balancing, satisfactory operation of the MLI and injection of clean sinusoidal grid current under any dynamic changes. Comprehensive simulation analysis is carried out considering a 15-level MLI structure. The practicality of the topological advancement for PV system is further confirmed by experimental tests under different dynamic conditions.

• Plesca, Adrian & Mihet-Popa, Lucian (2020). Thermal Analysis of Power Rectifiers in Steady-State Conditions. Energies. 13(8). doi: 10.3390/en13081942. Fulltekst i vitenarkiv Vis sammendrag

  Power rectifiers from electrical traction systems, but not only, can be irreversibly damaged if the temperature of the semiconductor junction reaches high values to determine thermal runaway and melting. The paper proposes a mathematical model to calculate the junction and the case temperature in power diodes used in bridge rectifiers, which supplies an inductive-resistive load. The new thermal model may be used to investigate the thermal behavior of the power diodes in steady-state regime for various values of the tightening torque, direct current through the diode, airflow speed and load parameters (resistance and inductance). The obtained computed values were compared with 3D thermal simulation results and experimental tests. The calculated values are aligned with the simulation results and experimental data.

• Bansal, Saumya; Zong, Yi; You, Shi; Mihet-Popa, Lucian & Xiao, Jinsheng (2020). Technical and economic analysis of one-stop charging stations for battery and fuel cell EV with renewable energy sources. Energies. 13(11), s. 1–15. doi: 10.3390/en13112855. Fulltekst i vitenarkiv
• Kumar, Raja; Devi, Priyanka; Chetri, Chandan; Vardan, Aanchal Singh S.; Elavarasan, Rajvikram Madurai & Mihet-Popa, Lucian [Vis alle 7 forfattere av denne artikkelen] (2020). Design and Characteristic Investigation of Novel Dual Stator Pseudo-Pole Five-Phase Permanent Magnet Synchronous Generator for Wind Power Application. IEEE Access. 8, s. 175788–175804. doi: 10.1109/ACCESS.2020.3025842. Fulltekst i vitenarkiv Vis sammendrag

  The main focus of this paper is to design and assess the characteristics investigation of Novel Dual Stator Pseudo-Pole Five Phase Permanent Magnet Synchronous Generator (NDSPPFP-PMSG) for wind power application. The proposed generator has a dual stator and two sets of five phase windings which enhance its power density and fault tolerant capability. The novelty of this generator is based on the fact that, eight magnetic poles are formed using only four poles of actual magnets on both the surfaces of the rotor. For the designing and optimal electromagnetic performance of the proposed generator, a Dynamic Magnetic Circuit Model (DMCM) is reported. To validate the results obtained from DMCM, Finite Element Method (FEM) has been opted owing to its high accuracy. For showing the performance superiority, the proposed generator is compared with two conventional generators namely, Dual Stator Embedded-Pole Five Phase (DSEPFP) and Single Stator Single Rotor Five Phase (SSSRFP) PMSG. To compare their performances, FEM results are considered. The electromagnetic performance namely, generated Electromotive Force(EMF), percentage(%) Total Harmonic Distortion(THD) of generated EMF, generated EMF vs speed, terminal voltage vs load current, electromagnetic torque developed on rotor vs time, %ripple content in the torque, and %efficiency vs load current are investigated for all the three generators. From these investigations, it is found that the power density (power to weight ratio) of the proposed generator is maximum.

• Sethuraman, Somalinga S; Santha, K.R.; Mihet-Popa, Lucian & Bharatiraja, Chokkalingam (2020). A Modified Topology of a High Efficiency Bidirectional Type DC–DC Converter by Synchronous Rectification. Electronics (Basel). 9(9). doi: 10.3390/electronics9091555. Fulltekst i vitenarkiv Vis sammendrag

  A modified Topology to acquire high efficiency of a bidirectional method of DC–DC converter of non-isolated approach is proposed. The modified circuit involves four numbers of switches with their body diodes, passive elements as two inductors as well as a capacitor and the circuit arrangements double boost converters to progress the voltage gain. The input current of the proposed topology divided amongst the two dissimilar values of inductors produces greater efficiency. In the step-down mode, an apparent lessening in voltage gain and also enhanced efficiency can be realized in the recommended system by expending a synchronous rectification. The modified topology shields the technique for presentation of easy control configurations and is used for truncated output voltage with a large current of energy storage systems in the renewable applications as well as hybrid energy source electric vehicle applications. The simulation of the projected structure has been conducted through MATLAB/Simulink software and has been corroborated through a 12 V/180 V, 200 Watts experimental prototype circuit.

• Rawa, Muhyaddin; Alkhalaf, Salem; Mihet-Popa, Lucian; Aboelsaud, Raef; Khurshaid, Tahir & Hassan, Abdurrahman Shuaibu [Vis alle 8 forfattere av denne artikkelen] (2020). An Efficient Scheme for Determining the Power Loss in Wind-PV Based on Deep Learning. IEEE Access. 9, s. 9481–9492. doi: 10.1109/ACCESS.2020.3046687. Fulltekst i vitenarkiv Vis sammendrag

  Power loss is a bottleneck in every power system and it has been in focus of majority of the researchers and industry. This paper proposes a new method for determining the power loss in wind-solar power system based on deep learning. The main idea of the proposed scheme is to freeze the feature extraction layer of the deep Boltzmann network and deploy deep learning training model as the source model. The sample data with closer distribution with the data under consideration is selected by defining the maximum mean discrepancy contribution coefficient. The power loss calculation model is developed by configuring the deep neural network through the sample data. The deep learning model is deployed to simulate the non-linear mapping relationship between the load data, power supply data, bus voltage data and the grid loss rate during power grid operation. The proposed algorithm is applied to an actual power grid to evaluate its effectiveness. Simulation results show that the proposed algorithm effectively improved the system performance in terms of accuracy, fault tolerance, nonlinear fitting and timeliness as compared with existing schemes.

• Fiore, Gaia; Mihet, Nicolae Lucian & Saponara, Sergio (2020). Exhaustive Modeling of Electric Vehicle Dynamics, Power train and Energy Storage/Conversion for Electrical Component Sizing and Diagnostic. Lecture Notes in Electrical Engineering. ISSN 1876-1100. 627, s. 433–440. doi: 10.1007/978-3-030-37277-4_50. Fulltekst i vitenarkiv
• Balasubramani, Gomathy; Thangavelu, Venkatesan; Chinnusamy, Muniraj; Subramaniam, Umashankar; Padmanaban, Sanjeevikumar & Mihet-Popa, Lucian (2020). Infrared Thermography Based Defects Testing of Solar Photovoltaic Panel with Fuzzy Rule‐Based Evaluation. Energies. 13(6). doi: 10.3390/en13061343. Fulltekst i vitenarkiv

Se alle arbeider i NVA

• Mihet-Popa, Lucian (2023). SMART GRIDS TECHNOLOGY AND APPLICATIONS. IntechOpen. ISBN 9781803556857. 182 s. Fulltekst i vitenarkiv Vis sammendrag

  This book provides a comprehensive overview of smart grid technology. It contains six chapters organized into three sections: “AC-DC Smart Hybrid Microgrid: Modelling, Control and Applications”, “Smart Distribution Systems: Methodologies, Realtime Platforms and Testing Methods”, and “Energy Storage Systems and Their Applications in Smart Grids”. Chapters address such topics as the advantages and disadvantages of AC/DC hybrid microgrids, DER components in an AC microgrid, methodologies for solving the reconfiguration and reactive power compensation dispatch in a smart distribution network, digital twin types, the different types of energy storage systems, and much more.

• Mihet-Popa, Lucian & Saponara, Sergio (2021). Power Converters, Electric Drives and Energy Storage Systems for Electrified Transportation and Smart Grid. MDPI. ISBN 9783036519364. 217 s. Fulltekst i vitenarkiv Vis sammendrag

  This book is a printed version of the Special Issue entitled “Power Converters, Electric Drives and Energy Storage Systems for Electrified Transportation and Smart Grid” on MDPI Energies journal. It presents 10 accepted papers from 18 submitted, as well as an Editorial, with authors from Europe, US, Asia, and Africa. The published papers are related to the emerging trends in solar power, energy storage, electric drives, and power electronic converters based on specific optimization and control methods and algorithms, with focus on electric vehicles and charging stations-based RES towards smart/micro grids. An extensive exploitation of renewable energy sources is foreseen for smart grid, as well as a close integration with the energy storage and recharging issues of the electrified transportation systems. It is expected that by 2050, around 65%–70% of the world’s population to live in urban areas. As our cities become bigger and smarter, this trend leads to new opportunities for specialized and flexible electric vehicles (EVs) designs, new vehicle architectures in order to ensure urban-readiness, such as compatibility with charging infrastructure, appropriate range, different implementation levels of infrastructure, and smart technology. In the next-generation of EVs, power and efficiency are critical. These factors drive the need for new power electronic converters, optimization of powertrain design and power management solutions to optimize system efficiency. Based on these assumptions, the huge interest coming from industry and research centers, and following our previous successful Special Issue with more than 20 papers published, which acquired in the last 3 years more than 400 citations and 50,000 views, we decided to open a new Special Issue. The Special Issue, entitled “Power Converters, Electric Drives and Energy Storage Systems for Electrified Transportation and Smart Grid” on MDPI Energies presents 10 accepted papers from 18 submitted, as well as an Editorial, with authors from Europe, US, Asia, and Africa. The published papers are related to the emerging trends in solar power, energy storage, electric drives and power electronic converters based on specific optimization and control methods and algorithms, with focus on electric vehicles and charging stations-based RES towards smart/micro grids. An extensive exploitation of renewable energy sources is foreseen for smart grid, as well as a close integration with the energy storage and recharging issues of the electrified transportation systems. Innovation at both algorithmic and hardware (i.e., power converters, electric drives, electronic control units, energy storage modules, and charging stations) levels are also proposed.

• Saponara, Sergio; Mihet-Popa, Lucian & Saletti, Roberto (2021). DC & Hybrid Micro-Grids. MDPI. ISBN 9783036519753. 173 s. Fulltekst i vitenarkiv Vis sammendrag

  This book is a printed version of the papers published in the Special Issue “DC & Hybrid Microgrids” of Applied Sciences. This Special Issue, co-organized by the University of Pisa, Italy, and Østfold University College in Norway, has collected nine papers and the editorial, from 28 submitted, with authors from Asia, North America, and Europe. The published articles provide an overview of the most recent research advances in direct current (DC) and hybrid microgrids, exploiting the opportunities offered by the use of renewable energy sources, battery energy storage systems, power converters, innovative control, and energy management strategies.

• Mihet-Popa, Lucian & Saponara, Sergio (2020). Energy Storage Systems and Power Conversion Electronics for E-Transportation and Smart Grid. MDPI. ISBN 9783039364268. 492 s. Fulltekst i vitenarkiv

Se alle arbeider i NVA

• Mihet-Popa, Lucian; Ahmed, Ibrahim Abbas Elamen & Islam, Fayzul (2025). NIKT 2025 – Institutt for informasjonsteknologi og kommunikasjon – Høgskolen i Østfold. Fulltekst i vitenarkiv Vis sammendrag

  Our workshop focuses on how emerging digital tools and intelligent algorithms, grounded in artificial intelligence (AI) and machine learning (ML), can be harnessed to enhance research processes across disciplines. With the rapid growth of data and computational power, AI- and ML-driven solutions are becoming indispensable for data analysis, pattern recognition, prediction, optimization, and decision support in research. The importance of these workshops lies in their role as collaborative arenas where researchers, practitioners, and students can share insights, test new ideas, and build networks. By tackling both theoretical advances and practical applications, our workshops contribute directly to the overarching goals of NIKT: fostering interdisciplinary collaboration, strengthening Norway’s ICT research landscape, and preparing society for rapid digital transformation. The relevance of this topic to NIKT is twofold. First, it strengthens the ICT research community by providing a platform for discussing state-of-the-art methods, tools, and frameworks that can improve the quality, efficiency, and reproducibility of research. Second, it bridges the gap between theory and practice by highlighting concrete applications—ranging from healthcare, climate science, and engineering to the humanities—showing how AI and ML can accelerate discovery and innovation. By bringing together researchers, practitioners, and students, the workshop fosters interdisciplinary collaboration, encourages knowledge transfer, and equips participants with insights into deploying smart algorithms and digital tools responsibly and effectively. Ultimately, this aligns with NIKT’s mission of advancing ICT research and ensuring that Norway remains at the forefront of digital transformation and innovation. Norsk IKT-konferanse for forskning og utdanning 24 - 26. November 2025 i Halden

• Mihet-Popa, Lucian (2025). Energy efficiency & sustainable utilization of resources in Green Transition. Fulltekst i vitenarkiv Vis sammendrag

  We must not forget the climate crisis. It is difficult enough to solve one crisis – managing several crises at the same time is a huge challenge. In a world that is increasingly characterized by crises and unrest, the important work against climate change and the destruction of nature can quickly be forgotten. The green transition refers to the global shift toward sustainable economic systems that minimize environmental impact and prioritize long-term ecological balance. Two foundational pillars of this transition are energy efficiency and the sustainable utilization of resources. Energy efficiency means using less energy to perform the same task or produce the same outcome. It reduces energy waste and lowers greenhouse gas (GHG) emissions. Improving energy efficiency can cut global GHG emissions by over 40% by 2040, according to the International Energy Agency (IEA). It also lowers energy bills, reduces energy imports, and boosts energy security. Key Strategies: Building retrofits, Smart grids and metering, Efficient appliances and lighting, Industrial optimization. Sustainable utilization of resources involves using natural resources—like water, minerals, biomass, and fossil fuels—in a way that meets present needs without compromising the ability of future generations to meet theirs. Key Approaches: Circular economy practices, Renewable energy adoption, Sustainable agriculture and forestry, Eco-design and green materials. Benefits: reducing environmental degradation and biodiversity loss, enhances economic resilience by reducing reliance on finite resources, supports social well-being through cleaner environments and resource equity. Energy efficiency and sustainable resource use are synergistic: • Efficient systems require fewer raw materials and generate less waste. • Sustainable materials can reduce the energy demand of manufacturing and end-of-life disposal. • Together, they contribute to carbon neutrality, economic competitiveness, and environmental justice.

• Irimia, Oana; Tomozei, Claudia; Mihet-Popa, Lucian; Panainte-Lehadus, Mirela; Mosnegutu, Emilian & Ojog, Oana (2025). Implementation of the Circular Economy Concept in the Framework of a Retail Company with Construction Materials. Fulltekst i vitenarkiv
• Islam, Fayzul; Abbas, Ibrahim A & Mihet-Popa, Lucian (2025). Demand-Side Management in Residential Buildings: Load Shifting and Cost Savings via a Cloud-Based IoT-BEMS. doi: https:/ieeexplore.ieee.org/document/11221160. Fulltekst i vitenarkiv
• Ahmed, Ibrahim; Pedersen, Andreas & Mihet-Popa, Lucian (2024). Smart Microgrid Optimization using Deep Reinforcement Learning by utilizing the Energy Storage Systems. Fulltekst i vitenarkiv Vis sammendrag

  The need for power is expanding quickly, and as fossil fuels are depleted, alternatives based on renewable energy are emerging. In recent years, microgrids, which are based on distributed generation and storage systems, have been on an increasing trend. This generates various new opportunities, one of which is the capacity to monitor, control, and regulate the energy flow inside and outside of the microgrid. By making microgrid’s distributed energy resources (DERs) and energy storage components economically viable with artificial intelligence and machine learning incorporated into the cost-optimization process, the demand for and growth of these technologies will be accelerated significantly. This paper focuses on employing reinforcement learning (RL) algorithms to control energy flow in an AC microgrid. By incorporating artificial intelligence and machine learning into the energy management system (EMS), the paper aims to optimize costs and facilitate the integration of renewable energy sources. The RL agent is designed to trade energy with the main grid, taking advantage of the energy storage system and achieving cost savings. The RL agent is tested using real spot prices data in Norway from a simulation model that combines Python and MATLAB-Simulink software programs for efficient co-simulation technique. Results show significant cost savings of around 14% for a simple model and 7.5% for a complex dynamic model. 10.1109/SGRE59715.2024.10428874

• Mihet-Popa, Lucian (2023). An IoT communication platform for interactive buildings energy management system. Fulltekst i vitenarkiv Vis sammendrag

  More than 40% of the world’s energy is used in buildings, from which 50% of energy is wasted because of non-existing or inefficient building energy management system (BEMS). By using a BEMS energy consumers are more connected, better controlled, monitored and managed, and the smart building has emerged. This paper deals with development of an IoT communication platform for building energy management systems. This is done by using an edge/cloud-computing architecture based on communication modules and service providers. A lab setup with real-time interfaces and data processing, for monitoring and controlling the power generation and consumption in different buildings, will be designed to validate the platform.

• Mihet-Popa, Lucian & Ahmed, Ibrahim (2023). Model Predictive Control of a Packed-U-cells Inverter with PV, Boost and Bidirectional Rectifier for Solid-State Transformers. Fulltekst i vitenarkiv Vis sammendrag

  Balancing the power flow in a three-phase system is one of the challenges in distribution networks, which is even more exacerbated with the widespread adoption of renewable energy sources (RES) and the development of smart grids. The transformer is one of the fundamental devices in power distribution that provides a means to link high-voltage, medium-voltage, and low-voltage networks in addition to galvanic isolation. Classical transformers utilize magnetic coupling with a turn ratio between coils to achieve this basic functionality, but they are bulky, expensive, and do not provide additional smart features. The use of a power electronics transformer (PET), also called a solid-state transformer (SST), has been introduced in the literature using a three-phase to single-phase converter to solve this problem. However, the focus was mainly on the inverter and a basic diode rectifier was used without RES integration. This paper bridged this gap by replacing it with a bidirectional converter and investigating its performance using solar power connected to the DC-link of the three-phase to single-phase solid-state transformer. The bidirectional SST was verified using simulations and the results show that the SST is able to maintain the balance between the three-phase system and the integrated renewable sources while providing bidirectional power flow with high efficiency and low Total Harmonic Distortion.

• Mihet-Popa, Lucian & Saponara, Sergio (2021). Power Converters, Electric Drives and Energy Storage Systems for Electrified Transportation and Smart Grid Applications. Energies. doi: 10.3390/en14144142. Fulltekst i vitenarkiv
• Saponara, Sergio; Saletti, Roberto & Mihet-Popa, Lucian (2020). Recent Trends in DC and Hybrid Microgrids: Opportunities from Renewables Sources, Battery Energy Storages and Bi-Directional Converters. Applied Sciences. doi: 10.3390/app10124388. Fulltekst i vitenarkiv Vis sammendrag

  This editorial manuscript reviews the papers accepted for publication in the Special Issue “DC & Hybrid Microgrids” of Applied Sciences. This Special Issue, co-organized by the University of Pisa, Italy and Østfold University College in Norway, has collected nine papers from 25 submitted, with authors from Asia, North America and Europe. The published articles provide an overview of the most recent research advances in direct current (DC) and Hybrid Microgrids, exploiting the opportunities offered by the use of renewable energy sources, battery energy storage systems, power converters, innovative control and energy management strategies.

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