Optimal power flow control variables using slime mould algorithm for generator fuel cost and loss minimization with voltage profile enhancement solution

Abstract

This paper presents a new nature-inspired metaheuristic technique namely Slime Mould Algorithm (SMA) which is inspired from the swarming behavior and morphology of slime mould in nature to solve a practical optimal power flow (OPF) problem. OPF is a highly non-linear complex optimization problem in the power system. SLM algorithm is used to determine the best values of control variables of which a selected objective function is minimized such as costs of conventional power generation minimization, active power loss reduction and improvement of the voltage profile. In the presented paper three case studies of IEEE 30-bus, IEEE 57-bus systems and large Algerian electrical test system DZ114 to show the effectiveness of this novel technique. The results of this research prove that SMA outperforms other techniques in terms of fuel cost minimization, reduction of active power losses and voltage deviation improvement.