Hybrid Intelligence Techniques for Unit Commitment of Microgrids

Optimal scheduling of the distributed generation (DG) sources for a microgrid is very essential for the economical and a balanced load sharing operation of the same. Various classical and evolutionary optimization techniques are being used to solve this scheduling problem. This paper deals in performing energy management of a rural microgrid test system using hybrids of Grey wolf optimizer (GWO). GWO is first modified (MGWO) as mentioned in literature. Further MGWO is amalgamated with sine cosine algorithm (SCA), particle swarm optimization (PSO) and crow search algorithm (CSA) to perform the optimization. All of numerical results, pictorial and statistical data point towards the superiority of the proposed MGWOPSO among the four other optimizers used.