An Improved Artificial Bee Colony Algorithm-based Configuration Optimization of a Remote Microgrid Considering Renewable Energy Systems

This paper proposes a configuration optimization technique for a remote microgrid considering renewable energy systems based on an improved artificial bee colony (IABC) algorithm. Typically, diesel generators are used to supply load demands to remote areas. This does not bring economic and environmental benefits in the context of fossil fuel resources being gradually depleted and environmental pollution problems increasing. The configuration optimization of the remote microgrid is based on a minimization of the cost of energy (COE) of the system. The considered renewable energy system includes wind turbine (WT) systems and solar photovoltaic (PV) systems. The obtained optimization results with the IABC algorithm are compared to those by using an artificial bee colony (ABC) algorithm, a genetic algorithm (GA), and a particle swarm optimization (PSO) algorithm. The comparisons confirm the effectiveness of the proposal.