Integration of Induction Generator Based Distributed Generation in Power Distribution Networks Using a Discrete Particle Swarm Optimization Algorithm

Abstract

An induction generator always absorbs lagging reactive power from the power network. In most previous power system optimization studies involving induction generator based distributed generation, this generator reactive power demand is calculated using an approximate empirical formula. In addition, shunt compensation capacitors have not been considered as part of the network optimization study. In this article, the use of the per phase equivalent circuit of the induction generator is proposed to compute its reactive power requirement, thus providing a more accurate estimation. A discrete particle swarm optimization algorithm is then employed to address the problem of simultaneous integration of the induction generators and shunt compensation capacitors. The proposed algorithm has the advantage of being able to cope with a mixed search space optimization problem of integer, discrete, and continuous variables. The study is carried out on a standard 69-bus benchmark distribution network. Results show that the use of the approximate empirical formula leads to an underestimation of the machine reactive power demand. The inclusion of shunt compensation capacitors in the optimization process results in lower network reactive power flows with improved network power losses, improved voltage profile, and increased levels of distributed generation integration.