Weighted elitism based Ant Lion Optimizer to solve optimum VAr planning problem

Abstract

In this paper, a newly proposed Ant-Lion Optimizer (ALO) is applied to solve Optimal Reactive Power Dispatch (ORPD) problem of power system. The ORPD is a VAr planning problem and is a highly non linear, non convex, challenging optimization problem; usually devised as constrained Optimal Power Flow (OPF). This paper also proposes the improvement in the search capability of ALO. A novel weighted elitism concept is introduced in the elitism phase of the original ALO to improve the exploration property of the algorithm. The proposed Modified ALO (MALO) intelligently balances both exploration and exploitation, which enhances the hunting capability of ALO. Both ALO and MALO is used to determine the optimal settings of generator voltages, tap positions of tap changer transformers and VAr output of shunt capacitors to optimize objectives: like, the active power loss, total voltage deviation and voltage stability index. The proposed algorithm is programmed and simulated on MATLB and tested on IEEE-30 and 57 bus systems. The results are compared with ALO and other methods. The effectiveness of MALO is further verified by solving few benchmark mathematical functions. The numerical results reveal that, MALO gives better optimum solutions for the benchmark functions compare to original ALO and outperforms several other methods used in the literature to solve ORPD problems. The t-Test and parametric analysis confirms the robustness and consistency of the MALO over ALO and other similar methods.