In this article, a new single-phase multilevel inverter is introduced with a reduced number of power switches and reduced voltage stress on power switches. The proposed topology consists of four input dc sources and nine semiconductor switches (eight unidirectional and one bidirectional switch). The topology can be used for asymmetrical voltage source configuration to generate seventeen voltage levels. The extended topology is constructed by a series connection of the topology circuit to produce higher voltage levels with less voltage stress on the switches without modifying the existing structure. Comparison is made with traditional and recently introduced topologies based on the number of power switches, dc sources, total blocking voltage of switches, and gate driver circuits, to prove the proposed topology's superiority. A simple nearest level modulation has been deployed as the switching scheme. Validation on the viability of the proposed topology has been carried out through simulation and hardware experimental setup.

Voltage source Multilevel Inverters (MLIs) are vital components for medium voltage and high-power applications due to their advantages like modularity and better power quality. However, the number of components used is significant. In this paper, an improved asymmetrical multilevel inverter topology is proposed producing 17-levels output voltage utilizing two dc sources. The circuit is developed to reduce the number of isolated dc-sources used without reducing output levels. The circuit utilizes six two-quadrant switches, three four-quadrant switches and four capacitors. The capacitors are self-balancing and do not require extra attention, i.e. the control system is simple for the proposed MLI. Detailed analysis of the topology under linear and non-linear loading conditions is carried out. Comparison with other similar topologies shows that the proposed topology is superior in device count, power quality, Total Standing Voltage (TSV), and cost factor. The performance of the topology is validated for different load conditions through MATLAB/Simulink environment and the prototype developed in the laboratory. Furthermore, thermal analysis of the circuit is done, and the losses are calculated via PLECS software. The topology offers a total harmonic distortion (THD) of 4.79% in the output voltage, with all the lower order harmonics being less than 5% complying with the IEEE standards.

Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing dependence on non-endogenous resources. In addition, vehicle-to-grid (V2G) technology has made EVs a potential form of portable energy storage, alleviating the random fluctuation of renewable energy power. This paper simulates the optimal design of a photovoltaic/wind/battery hybrid energy system as a power system combined with an electric vehicle charging station (EVCS) using V2G technology in a grid-connected system. The rule-based energy management strategy (RB-EMS) is used to control and observe the proposed system power flow. A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid (${\mathrm{E}}_{\mathrm{S}\mathrm{O}\mathrm{L}\mathrm{D}}$). This research uses a collection of meteorological data such as solar radiation, temperature, and wind speed captured every ten minutes for one year for a government building in Al-Najaf Governorate, Iraq. The results indicated that the optimal configuration of the proposed system using the MOIAOA method consists of eight photovoltaic modules, two wind turbines, and thirty-three storage batteries, while the fitness value is equal to 0.1522, the LCOE is equal to 2.66 × ${10}^{-2}$ USD/kWh, the GCF is equal to 7.34 × ${10}^{-5}$ kWh, and the ${\mathrm{E}}_{\mathrm{S}\mathrm{O}\mathrm{L}\mathrm{D}}$ is equal to 0.8409 kWh. The integration of RESs with an EV-based grid-connected system is considered the best choice for real applications, owing to their remarkable performance and techno-economic development.

This project presents a sensorless control method for Permanent Magnet Synchronous Motor (PMSM) drives using Extended Kalman Filter (EKF). The study, design, analysis and modeling have been made in order to obtain an estimator of speed and rotor position. The PMSM drives is mostly used in a lots of automation control field due to its benefit like high density and performance motion control for high speed application and better accuracy. However, the conventional motor drives control requires the mechanical sensor or speed sensor to measure the rotor speed and feed it back to the controller in order to achieve the required speed control. The current issue is the mechanical sensor such as tachometer and encoder that used to measure the quantities speed and rotor position are usually too expensive, decrease the stability of the system and raise the budget. Thus, the sensorless control technique using EKF has been more emphasized now in the research field. The main objective of this project is to model and simulate based on Extended Kalman Filter (EKF) sensorless control for PMSM drives and to analyze the performance of sensorless operation related to the Extended Kalman Filter (EKF) of the PMSM drives in term of speed of the motor, rotor position, current and motor's torque. The simulation is carried out using MATLAB/Simulink to measure the overall motor drives performance. The simulation results show that sensorless PMSM drives using EKF have great efficiency, better accuracy and reliable operation system.