Solution of the Multi-Objective Optimal Power Flow Problem Using Oppositional-Based Algorithm

Abstract

An efficient optimal power flow (OPF) algorithm allows the finest setting of the plant by solving multi-objective optimization problem to minimise the overall operating cost. This paper proposes the quasi oppositional backtrack search algorithm (QOBSA) for optimal setting of OPF control variables. The QOBSA is stochastic algorithm which gives committed and robust results compared to the traditional methods. This technique has been implemented to test the control parameters for the IEEE 30-bus with single and multi-objective functions like the minimization of fuel cost, minimization of total voltage deviation (TVD), voltage stability enhancement, emission reduction, and multi-fuel cost minimization. The result provides better voltage profile at every bus based on L-index which in turn greatly reduces the burden on load buses. The QOBSA code has been developed in the MATLAB platform and tested with the help of IEEE 30-bus and the outcomes have been compared with ongoing literature.