In this study, an optimization algorithm called chaotic turbulent flow of water-based optimization (CTFWO) algorithm is proposed to find the optimal solution for the optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a complicated, mixed-integer nonlinear optimization problem, comprising control variables which are discrete and continuous. The CTFWO algorithm is used to minimize voltage deviation (VD) and real power loss (P_loss) for IEEE 30-bus and IEEE 57-bus power systems. These goals can be achieved by obtaining the optimized voltage values of the generator, the transformer tap changing positions, and the reactive compensation. In order to evaluate the ability of the proposed algorithm to obtain ORPD problem solutions, the results of the proposed CTFWO algorithm are compared with different algorithms, including artificial ecosystem-based optimization (AEO), the equilibrium optimizer (EO), the gradient-based optimizer (GBO), and the original turbulent flow of water-based optimization (TFWO) algorithm. These are also compared with the results of the evaluated performance of various methods that are used in many recent papers. The experimental results show that the proposed CTFWO algorithm has superior performance, and is competitive with many state-of-the-art algorithms outlined in some of the recent studies in terms of solution accuracy, convergence rate, and stability.

Recently, there was a great focus on integrating renewable energy sources (RESs) into electrical power systems (hybrid systems) due to their many environmental and economic advantages. The output of most of these RESs is DC; some power electronic devices, including inverters, must be used to integrate these RESs into the electrical grid. Any maloperation, faults, or improper control in these power electronic devices will enormously affect these hybrid systems’ performance. This paper aims to mitigate the misfire and fire-through faults that occur at the switching of the inverter that connects three renewable sources: PV, wind, and the fuel cell to the grid. This mitigation of such inverter faults (misfire and fire-through) is performed through optimal tuning of the PI controller driving a dynamic voltage restorer (DVR) connected at the system’s AC side. The optimization technique used is particle swarm optimization (PSO). While mitigating these two inverter faults using the PI-PSO controller for the DVR, improved system performance through voltages, currents, and powers waveforms is achieved. Besides, the three renewable sources were kept in continuous operation without disconnection from the system during these faults.

Generating electric power using solar thermal systems is effective, particularly for countries with high solar potential. In order to decide on a relevant location to implement the solar tower plant and develop the mathematical model of a no-blocking heliostat field, a meteorological assessment was discussed in this paper. In addition, a parametric study was examined to evaluate the effect of the designed parameters (heliostat size, heliostat height from the ground, tower height, receiver aperture, and the minimum radius) on the solar field’s performance. The preliminary solar field was then compared to the final design using the optimal design parameters. The obtained results showed that “Tamanrasset City” satisfied the necessary conditions for implementing a solar tower plant. According to preliminary solar field generation, no heliostat blocked its neighbor with a blocking efficiency of 100%. An analysis of its performance revealed that the optimized solar field would be capable of producing 15, 6571 MW, operating at an optical efficiency of 76.95%, and the enhancement rate of both efficiency and power output was 8.1%.