Risk assessment of photovoltaic distribution network based on adaptive kernel density estimation and cumulant method

Abstract

In order to efficiently and accurately evaluate the out of limit risk of photovoltaic power distribution network, the adaptive kernel density estimation (AKDE) method is introduced to fit the actual light intensity sequence, and the probability distribution model of photovoltaic power station output characteristics is established. At the same time, the Cornish–Fisher series combined with the cumulant method (CM) is used to calculate the probabilistic power flow of photovoltaic distribution network, the accuracy of probabilistic power flow calculation (PPFC) is verified by Monte Carlo Method (MCM), the system level voltage out of limit risk index (VOLRI) and branch power flow out of limit risk index (BPFOLRI) are established. Finally, MATLAB is used to verify the accuracy and efficiency of the algorithm for photovoltaic distribution network risk assessment.