Swarm-Inspired Artificial Bee Colony Algorithm for Solving Optimal Power Flow with Wind Farm

Abstract

In this paper, an enhanced artificial bee colony (ABC)-based algorithm is proposed for solving optimal power flow (OPF) with wind farm. The OPF calculations determine optimal values of control variables and system quantities for secure and economic system operation considering various limitations with wind farm. In the OPF problem, wind farm is modeled as an aggregate permanent magnet synchronous generator and subsequently modeled as an aggregate squirrel cage induction generator. The proposed algorithm is developed by the combined application of Gaussian and Cauchy probability distributions in ABC algorithm and hence termed as swarm-inspired artificial bee colony (SIABC) algorithm. The performance of the proposed SIABC algorithm is compared with particle swarm optimization (PSO) and ABC algorithms. The optimal solutions for adopted IEEE 30-bus system with wind farm and adopted Indian Utility 66-bus system obtained by these algorithms are compared and analyzed. The analysis reveals that the proposed SIABC algorithm is relatively simple, reliable and faster in convergence than PSO and ABC algorithms.