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<span lang="MS">This paper presents a Stand-alone Hybrid Renewable Energy System (SHRES) as an alternative to fossil fuel based generators. The Photovoltaic (PV) panels and wind turbines (WT) are designed for the Malaysian low wind speed conditions with battery Energy Storage (BES) to provide electric power to the load. The appropriate sizing of each component was accomplished using Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques. The optimized hybrid system was examined in MATLAB using two case studies to find the optimum number of PV panels, wind turbines system and BES that minimizes the Loss of Power Supply Probability (LPSP) and Cost of Energy (COE). The hybrid power system was connected to the AC bus to investigate the system performance in supplying a rural settlement. Real weather data at the location of interest was utilized in this paper. The results obtained from the two scenarios were used to compare the suitability of the NSGA-II and MOPSO methods. The NSGA-II method is shown to be more accurate whereas the MOPSO method is faster in executing the optimization. Hence, both these methods can be used for techno-economic optimization of SHRES. </span>

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Summary Electric vehicle (EV) systems are the promising future transportation system as they play a key role in reducing the atmospheric carbon emission, and it becomes the focal point of research and development in the current epoch. This paper presents the design and development of three‐port dc‐dc buck‐boost converter (TPB2C) applicable for EV. The main feature of the proposed converter is its ability to handle diversified energy sources of different voltage and current characteristics with high output gain. The designed single stage converter with reduced components count can be operated in buck, boost, and buck‐boost mode with partial bidirectional power flow capability. In addition, the TPB2C converter could provide buck and boost output simultaneously unlike its counterparts which can output either buck or boost output. In buck mode, the suggested topology charges the battery and thereby eliminates a separate battery management system. Roof top photovoltaic panel and battery are the two input sources for the suggested converter. A small‐signal model of the converter is developed using state‐space approach, and the steady‐state performance of the converter is analyzed comprehensively. The device level simulations carried out in MATLAB‐Simulink and the experimental laboratory prototype model are validated using a dSPACE1104 real‐time digital controller.

This paper work exploits a new dual openwinding three-phase multilevel inverter configuration suitable for high power medium-voltage applications. Modular structure comprised of standard three-phase voltage source inverter (VSI) along with one additional bi-directional semiconductor device (MOSFET/IGBT) per phase and two capacitors with neutral point. Hence, introduces the additional voltage levels in each phase of the VSI. Further, this paper developed a modified single carrier five-level modulation (MSCFM) scheme in such way to overcome the complexity of standard space vector modulations, ready for implementation purpose. Proposed dual-inverter configuration generates multilevel outputs with benefit includes reduced THD and dv/dt in comparison to other dual-inverter topologies. Complete model of the multilevel ac drive is developed with simple MSCFM modulation in Matlab/PLECs numerical software. Preliminary results are provided in this paper confirm the suitability of investigation for real implementation.