Quantifying the Impact of Different Parameters on Optimal Operation of Multi-Microgrid Systems

The multi-objective optimal power management of multi-microgrid systems is solved in this paper. Minimizing the total cost and emission of the system are considered as the objective functions. The multi-objective particle swarm optimization algorithm is applied on a multi-microgrid system that consists of four microgrids each includes diesel generators, wind turbines, photovoltaic units, battery, and local loads. The multi-microgrid system can exchange power with the electricity grid. Moreover, the adjacent microgrids in the multi-microgrid system can share power with each other. The impact of the variation of battery charging and discharging efficiency, the electricity price, the capacity of diesel generators and renewable-based units, the maximum exchangeable power between the multi-microgrid system and the electricity grid and the power sharing among adjacent microgrids on day-ahead units’ scheduling of multi-microgrid are evaluated through sensitivity analysis in simulation results.