Slime Mould Optimization Algorithm for optimal location and sizing of distributed generations

Abstract

In this paper, a new meta-heuristic slime mould algorithm (SMA) is developed for both location and size of distributed generation (DG) units. Total real power losses minimization is considered as a main objective considering DG units’ allocation and voltage profile kept within the acceptable limits. The main concept of the SMA algorithm is motivated by natural slime mould movement to search for its food as an objective. This approach works on a weighted positive and negative feedback-based bio-oscillator, to generate a network of nourishing veins of various diameters, to search its food resources selecting the optimal route. IEEE-30-bus test and 57-bus test systems are applied via implemented approach to achieve the optimized results. Both DG units’ allocation based SMA, and biogeography-based optimization (BBO) approaches simulated results are compared. The comparison illustrates the better optimization and efficacy of the implemented technique in terms of improvement in total installed capacity of DG units, optimal solution, and fast convergence rate.