Risk Assessment of Static Voltage Stability Based on Power Electronic Load Uncertainty Modeling

Abstract

As a typical representative of load-side power electronic technology, the increasing popularity of electric vehicles such as electric vehicles (EVs) on the static voltage stability of distribution networks cannot be ignored. According to the uncertainty of the space-time distribution of the charging load, this paper presented a risk assessment framework of static voltage stability in the power system that takes into account the uncertainty. Power Electronic Load uncertainty modeling consisted of three steps: Modified fuzzy cluster method (FCM), Cholesky decomposition and multi-dimension normal distribution sampling method were adopted to get initial load profile; A probability hyper-cone load growth model was proposed based on Monte Carlo method to simulate stochastic variation of loading direction and power factor; One evaluation system combining correlation coefficient with mutual information was established to divide buses into different groups according to the similarity degree of their load curve. When the load uncertainty model was established, it would be inserted into the proposed Monte Carlo - continuation power flow (MCCPF) algorithm. Two risks indexed focusing respectively on bus and entire system were proposed and would be calculated based on MCCPF performance results, an integrated risk assessment framework was then founded. Taking the 110kV power grid in Taiyuan City as an example, the static voltage stability risk assessment indicators of the EV access area power grid are analyzed, including the average network average load risk index and the node low-voltage load risk index, respectively describing the static voltage stability risks of the system and nodes, and the validity and effectiveness of proposed method is verified.