Optimal utility cooperation in the microgrids expansion planning

Abstract

Economic and technical justification made the government support the utility network's microgrid (MG) expansion. The government subsidy is shifted from renewable energy to MG expansion since they increase renewable generation in a controlled manner. In the proposed method, the utility designs the roadmap of the MGs expansion in the distribution grid. First, the MGs numbers and boundaries are determined based on the utility goals. The utility load points are clustered through the fuzzy clustering method (FCM) and then aggregated via the iterative process to form MGs. Then, the planning model is proposed to minimize the MGs cost while maximizing the utility subsidies. The energy and investment subsidies are modeled through the incentive and punishment mechanism based on the utility goals. Both microgrid cost and subsidy are optimized simultaneously. The proposed method investigates the long-term effect of government subsidies on the MGs expansion through the planning model. The uncertainty of load and renewable energy are modeled through the scenario-based model. In the result section, the subsidization efficiency of the utility is analyzed. The effect of the cost reduction of the DGs and ESSs due to the advances in their technology and the impact of ESSs number on the subsidy efficiency are analyzed. The result determines the roadmap for the government to make optimal decisions in the MGs expansion planning.