A multi-objective optimal sizing and siting of distributed generation using ant lion optimization technique

In this paper, a new optimization method is proposed to solve the optimal sizing and siting problem of distributed generation (DG) in a distribution system (DS). The optimization problem is solved using a new ant lion optimizer (ALO) with considering different objectives. These objectives are reduction of purchased energy cost from upstream network (due to DGs’ power generation), reliability improvement, reduction of DGs’ application cost, reduction of DS losses and reduction of buses’ voltage deviation. This problem is solved as a multi-objective optimization (MOO) in addition of a single-objective optimization (SOO). The proposed DGs optimal sizing and siting is implemented on 33 and 69-bus IEEE networks. The obtained results show that the ALO has the best performance in extracting the solution of DGs optimal sizing and siting problem in comparison to particle swarm optimization (PSO) and genetic algorithm (GA). Keywords: Optimal sizing and siting, Distributed generation, Ant lion optimizer, Reliabilit