Artificial Bee Colony based optimal management of microgrid

Due to ever increasing energy demand and expectation, microgrid has received a great attention. Microgrid can be viewed as a cluster of loads and parallel DG units installed at consumer´s sites. The main objective of this paper is to address on the issue of optimal operating strategy and cost optimization scheme for a microgrid using three evolutionary techniques, namely Particle Swarm Optimization (PSO), Craziness based Particle Swarm Optimization (CRPSO) and Artificial Bee Colony (ABC) algorithms. In this paper a microgrid with wind turbine, PV array, diesel engine, fuel cell and microturbine are studied. The proposed cost function considered are the cost of the emissions NO_x, SO₂ and CO₂, operating and maintenance cost as well as start- up costs of different sources. The total operating cost of the microgrid is minimized with the help of optimization techniques. It is seen from the results that the ABC based algorithm provides the best economic solution with the minimum use of diesel engine.