A novel method for optimal capacitor placement and sizing in distribution systems with nonlinear loads and DG using GA

摘要

A genetic algorithm (GA) is proposed for simultaneous power quality improvement, opti-mal placement and sizing of fixed capacitor banks in radial distribution networks with nonlinear loads and distributed generation (DG) imposing voltage-current harmonics. In distribution systems, nonlinear loads and DGs are often considered as harmonic sources. For optimizing capacitor placement and sizing in the distribution system, objective func-tion includes the cost of power losses, energy losses and capacitor banks. At the same time, constraints include voltage limits, number/size of installed capacitors (at each bus) and the power quality limits of standard IEEE-519. In this study, new fitness function is used to solve the constrained optimization problem with discrete variables. Simulation results for two IEEE distorted networks (18-bus and 33-bus test systems) are presented and solu-tions of the proposed method are compared with those of previous methods described in the literature. The main contribution of this paper is computing the (near) global solution with a lower probability of getting stuck at a local optimum and weak dependency on ini-tial conditions, while avoiding numerical problems in large systems. Results show that pro-posed method could be effectively used for optimal capacitor placement and sizing in distorted distribution systems.