BI-OBJECTIVE FUNCTION MICRO GRID OPTIMAL OPERATION USING A HYBRID ALGORITHM

Nowadays, given the rapid growth of socioeconomic issues, more emphasis is being placed upon providing the consumers with higher quality services. Consequently, many modern societies are seeking to use new energy management systems to reduce the environmental pollutions and operational costs resulting from electrical energy generation systems. So, benefiting from various renewable energy resources, Micro Grid (MG) could be considered as a substantial tool to reach such objectives. According to this matter, the present paper is aimed at introducing the, multiobjective Hybrid Big Bang - Big Crunch (HBB-BC) algorithm to be used for optimizing a sample MG. The problem is assumed to be an optimization problem with nonlinear multiple objectives, having different qualities and non-equal limitations in order to reduce the cost and distribution of pollutants. The proposed algorithm is applied in a sample MG and the results are compared with other optimizing algorithms such as particle swarm optimization (PSO) and Big Bang - Big Crunch (BB-BC).