A New Approach Meta-Heurestics Optimization Techniques to Solve Multi Objective Optimal Power Flow Problems

In this paper, a new approach meta-heuristic optimization technique has been proposed to solve multi objective optimal power flow (MOOPF). A Slime Mould Algorithm (SMA) is one of the new stochastic optimization methods inspired by the behaviour of the oscillation mode of slime mould in nature. This approach represents a new adaptive of Slime Mould Algorithm - called Multi Objective Slime Mould Algorithm (MOSMA) - was used to solve MOOPF problems. The authors solved several multi-objective functions using the suggested optimization method. The fuel cost, real power losses, and emissions are included in these objective functions. The proposed approach includes a few controls parameter and an easy structure. The highly constrained objectives can also be solved using MOSMA. The MOSMA employs a fuzzy membership technique to find the best compromise solution from all the produced Pareto front solutions. The proposed technique uses a crowding distance strategy to rank and arrange Pareto front solutions. Additionally, the MOSMA approach's ability is assessed, validated for bi- and tri-objectives, and tested on an IEEE 57-bus power system with four case studies. The simulation results demonstrate that the suggested methodology is efficient to produces well-distributed Pareto front solutions.