Stochastic Optimal Strategy for Power Management in Interconnected Multi-Microgrid Systems

Abstract

A novel stochastic strategy for solving the problem of optimal power management of multi-microgrid (MMG) systems is suggested in this paper. The considered objectives are minimizing the total cost and emission of the system. The suggested algorithm is applied on a MMG consisting of four microgrids (MG), each including fossil fuel-based generator units, wind turbine (WT), photovoltaic (PV) panel, battery, and local loads. The unscented transformation (UT) method is applied to deal with the inherent uncertainties of the renewable energy sources (RES) and forecasted values of the load demand and electricity price. The proposed algorithm is applied to solve the power management of a sample MMG system in both deterministic and probabilistic scenarios. It is justified through simulation results that the suggested algorithm is an efficient approach in satisfying the minimization of the cost and the environmental objective functions. When considering uncertainties, it is observed that the maximum achievable profit is about 23% less than that of the deterministic condition, while the minimum emission level increases 22%. It can be concluded that considering uncertainties has a significant effect on the economic index. Therefore, to present more accurate and realistic results it is essential to consider uncertainties in solving the optimal power management of MMG system.