Evaluating Influence of Variable Renewable Energy Generation on Islanded Microgrid Power Flow

With the proliferation of renewable energy, the uncertainty has challenged the continuous operation of microgrids; thus, it is of importance to tackle uncertainties in power system operation. In this paper, a global sensitivity analysis (GSA) method is proposed to evaluate the influence of uncertainties on the power flow of islanded microgrids (IMGs). First, a probabilistic power flow model for IMGs is established considering the droop-controlled distributed generation units and the uncertainties of renewable energy generation output and load demands. Then, the global sensitivity analysis is introduced to identify important variables that affect IMG power flow. In addition to conventional GSA indices, the Shapley value-based GSA index is designed to evaluate the influence of correlated input variables. Moreover, the sparse polynomial chaos expansion is used to establish the surrogate models of IMG power flow, which improves the efficiency of GSA. Finally, the proposed method is tested on the 33-bus and 69-bus IMG systems, and the simulation results are compared with those considering other methods. The rankings of random input variables that affect IMG power flow are given, and the influence of correlation between different variables is discussed.