Probabilistic power flow for distribution networks with photovoltaic generators

Based on Monte Carlo technique, this paper develops a probabilistic power flow (PPF) algorithm to evaluate the influence of photovoltaic (PV) generation uncertainty on distribution networks. Not only the randomness, but also the correlation of PV power and the moments when PV generators start and stop producing power in a day are taken into account with the presented method using the theory of conditional probability and nonparametric kernel density estimation. The measured power data of photovoltaic generator in Oregon State, USA and 34 node distribution test network are used to demonstrate the application of the presented method in PPF analysis.