ACTIVE POWER LOSS MINIMIZATION OF TRANSMISSION POWER SYSTEMS WITH WIND POWER PLANTS AND FACTS DEVICES

Abstract

This study focuses on solving the optimal power flow (OPF) problem on the transmission system with the objective of minimizing the active power loss (APL). To achieve the proposed objective, the study applies the Particle swarm optimization (PSO) algorithm and the constraint factor-based Particle swarm optimization (CF-PSO). To evaluate the effectiveness of the two methods in solving the OPF problem on an IEEE 30-node grid with the integration of renewable energy sources and reactive power compensation devices such as TCSC (Thyristor Controlled Series Compensator) and SVC (Static Power Compensator) using four different case studies. These cases consider the impact of integrating the components (renewable energy plants, TCSC, SVC) into the grid independently and together. Changing the system configuration in these cases leads to a significant change in the solution space of the problem, creating an ideal testbed to compare the performance of PSO and CF-PSO. The results show that CF-PSO outperforms the original PSO in both aspects: the stability of the optimization process and the speed of convergence to the optimal solution. Specifically, CF-PSO can reduce the active power loss by 4.8%, 6.6%, 0.9% and 0.4% compared to PSO in the four studied cases, respectively. These results confirm that CF-PSO is an effective and powerful optimization tool for the OPF problem in modern power systems, especially when renewable energy sources and compensation devices are involved. This study provides an insight into the potential of CF-PSO in solving complex optimization problems in the energy sector.