Optimal Sizing of an Islanded Micro-Grid Using Meta-Heuristic Optimization Algorithms Considering Demand-Side Management

This paper proposes a novel modeling approach for optimal sizing of the components of an islanded micro-grid subject to satisfying a reliability index for meeting the loads. The proposed micro-grid incorporates photovoltaic arrays, wind turbines, a battery bank, an inverter, and an electric vehicle (EV) charging station. A demand-side management mechanism based on a deferrable load program is implemented and a model reduction technique is also utilized to mitigate the computational cost. Three different optimization algorithms, namely the whale optimization algorithm (WOA), particle swarm optimization (PSO), and the genetic algorithm (GA) are considered in this study to minimize the total cost of the system. The simulation studies have shown that although the WOA reduces the computational burden and requires much lower iterations compared with PSO and GA, it converges to sub-optimal solutions; therefore, it is not a good option for micro-grid planning purposes. Moreover, the results demonstrate that by charging coordination of EVs and deferring a pre-determined portion of the residential loads, overloading can be avoided and available components can be utilized better, which in turn reduces the sizes of the components and total cost of the system.