PNNL

Abstract

The increasing integration of renewable energy resources such as wind and solar may drive the electric power grid towards weak grid conditions, which may cause potential grid stability and reliability issues. The variation and uncertainty of renewable energy increases the difficulty to identify weak grid issues. This paper proposes an efficient method to analyze the impact of uncertain renewable energy on grid strength. The proposed method uses probabilistic collocation method (PCM) to approximate the results of grid strength assessment under uncertain renewable generation, in order to reduce the computational burden without compromising the result accuracy when compared with traditional Monte Carlo simulation (MCS). To improve the accuracy of the approximation results, the proposed method integrates the K-means clustering technique with PCM to select the approximation samples of input variables. The efficacy of the proposed method is demonstrated by comparison with MCS on the modified IEEE 9-bus system and modified IEEE 39-bus system with multiple renewable generators.