Two Stage Optimal Capacitors Placement and Sizing Using Differential Evolution Particle Swarm Optimization

Abstract

Installing capacitors in a large unbalanced electrical distribution system will indeed improves the performance of the system in terms of its voltage profile and real power loss stability. However, determining the suitable locations for capacitors installation with an appropriate sizing in an unbalanced electrical distribution system involves an intricate process. This impediment can be resolved by implementing an optimal capacitors placement and sizing. The proposed technique is a highly nonlinear optimization problem which requires discrete and multi-dimensional control variables of capacitor locations and sizes. This paper proposed a new artificial intelligence approach used to reduce the total line real power loss and total real power consumption while maintaining the voltage profile along the feeders. It was done by integrating the circuitry schematic diagram of an unbalanced electrical distribution system modeled in SIMULINK® software with the computational programming based differential evolution particle swarm optimization (DEPSO) for optimal capacitors placement and sizing developed under the MATLAB® software. In this study, pre-selection of the capacitor locations can be considered as the first stage of the proposed concept and it is commenced prior to the optimization process performed by the DEPSO algorithm considered as the second stage of the proposed concept. A modified IEEE 13-bus unbalanced radial distribution system is used verify effectiveness of the proposed technique in solving the problem. The results will be discussed notably through comparative studies on the objective function of total cost and performance of the DEPSO technique.