Maximum Loadability of Islanded Microgrids With Renewable Energy Generation

Abstract

A microgrid (MG) is a small-scale power system which is fed by constrained distributed generation (DG) units and its continuous operation is affected by the variability of available generation resources. In this paper, a global sensitivity analysis (GSA) method is proposed to evaluate the impact of variable energy resources on the maximum loadability of islanded MGs (IMGs). First, a probabilistic optimization problem is formulated to calculate the IMG load margin considering the droop characteristics of DG units and uncertainties of renewable generation, loads and distribution feeder parameters. Next, the global sensitivity (GS) is introduced that can identify the impact of independent and correlated variables on the IMG loadability. Last, the sparse polynomial chaos expansion method is used to obtain the probabilistic models for IMG load margins, and an efficient GSA method is proposed to calculate the GS of IMG loadability to prevailing variables. The probabilistic models are considered for IMG input variables and the impact of variable correlations on IMG loadability is analyzed. The proposed method for calculating the maximum loadability is tested using a 33-bus IMG and the results are compared with those of other GSA and local sensitivity analysis methods.