Optimal Placement, Replacement and Sizing of Capacitor Banks in Distorted Distribution Networks by Genetic Algorithms

Abstract

This paper presents a new genetic algorithm (GA)-based approach for the simultaneous power quality improvement and optimal placement and sizing of fixed capacitor banks in radial distribution networks in the presence of voltage and current harmonics. The objective function includes the cost of power losses, energy losses and that of the capacitor banks. Constraints include voltage limits, number/size and locations of installed capacitors (at each bus and the entire feeder) and the power quality limits of standard IEEE-519. Candidate buses for capacitor placement are selected based on an initial generation of chromosomes. Using a proposed fitness function, a suitable combination of objective and constraints is defined as a criterion to select (among the candidates) the most suitable buses for capacitor placement. A genetic algorithm computes improved generations of chromosomes and candidate buses until the solution is obtained. Simulation results for two IEEE distorted networks are presented and solutions of the genetic algorithm are compared with those of the maximum-sensitivities-selection (MSS), the maximum sensitivities selection-local variations (MSS-LV), and the fuzzy set algorithms. The main contribution of this paper is the computation of the near global solution, with weak dependency on initial conditions.