This paper proposed a modified algorithm for controlling a single-phase split-source inverter. The proposed algorithm is a modified model predictive control based on Harris Hawks optimization, where the AC output voltage, the DC-link voltage, and the DC input current are controlled within one cost function. Hence, the discrete time models of both AC-side and DC-side are obtained. For proper operation of the modified MPC, each error term within the cost function has a weighting factor. Harris Hawks optimization technique is used to determine the weighting factors at each term of the cost function. The proposed algorithm is validated using MATLAB/Simulink. Simulation results show that the system has succeeded in controlling AC load voltage, input current, and achieving constant DC-link voltage over a wide operating range.

In this paper an efficient, compact, and cheap power source design for an off-grid PV water pumping system is investigated. The proposed system consists of a PV array, battery, three-port converter (TPC), three-phase voltage source inverter, and induction motor pump. Power is extracted from PV sources during the daytime and used to charge batteries through the three-port converter, then used later to supply load during the nighttime. An intelligent MPPT method is used to obtain PV maximum power; a jellyfish optimization technique with different control algorithms is used to optimize and tune controllers’ parameters among the system. Different modes for the TPC are discussed depending on PV power availability. The proposed system is simulated to assess system performance under different conditions; also the system is efficient with reduced number of components than conventional converters. A complete unified power management over PV input port, battery port, and load port has occurred for all operation modes. At all operation modes, the system has been feeding load without any unmet loads. A real case study in Al-Kharijah oasis is studied and simulation results are listed; for the Dom case DC bus ripple factor voltage percentage equals 0.8%, in the Dim case equals 3%, and in the Siso mode equals 9%.

This paper presents an improved PI-controller for minimizing the ripple torque of switched reluctance motor (SRM) drives in electric vehicle applications. The motor speed is controlled by an optimized proportional-integral PI-controller in the outer loop, and the motor torque is controlled by an additional optimized PI-controller with a hysteresis controller in the inner loop. The controller gains are obtained based on a Harris Hawk's Optimization (HHO) Because of the nonlinear characteristics of the SRM. The objective function is to minimize the integration of the absolute error (IES). A 6/4 SRM is used to investigate the performance of the motor with the proposed controller using Matlab/Simulink toolbox. According to the simulation results, the suggested controller achieves to acceptable ripple torque and achieves the target speed.

Because of the increasing and escalating demand on energy sources, utilizing renewable energy sources efficiently becomes mandatory. This paper aims to construct and discuss efficient and low-cost configuration of standalone PV water pumping system with three-phase induction motor. This configuration is achieved by using optimized PI-controllers with the Jellyfish optimizer and a high gain DC to DC converter with maximum power point tracking technique to extract maximum power from the PV system. In addition to the high gain DC to DC converter, the proposed system consists of PV array, DC to DC bidirectional converter with batteries in order to save excess PV power and reuse it when there is no enough output power for the system, three-phase inverter, three-phase induction motor, and pump to drive the water. The proposed system succeeded to keep the total harmonic distortion for the AC output voltage within 0.61%, and keep DC bus voltage ripple factor within 0.2%, both are within acceptable limits. The system is designed, modeled, and simulated in detail using MATLAB/Simulink software to evaluate the performance under fast variations of climatic profile.