Two-stage distributionally robust assessment method for distributed PV hosting capacity of flexible distribution networks

Abstract

The large-scale grid-connection of distributed PV has brought great challenges to distribution network. The traditional stochastic optimization and robust optimization have conservative problems in dealing with the uncertainty of distributed PV. Therefore, based on the historical scenario data of PV output, this paper proposes a two-stage distributionally robust assessment method for distributed PV hosting capacity of distribution networks considering demand response. Firstly, a weighted K-means algorithm is used to cluster the historical data of distributed PV output to obtain typical scenario data and establish the demand response model of electricity price incentive. In order to maximize the grid-connected capacity of distributed PV, multiple operational constraints and adjustment strategies in flexible distribution network were considered. Then, a two-stage distributionally robust assessment model for distributed PV hosting capacity of flexible distribution network is established, and the column-and-constraint generation algorithm is used for iterative solution. The effectiveness of the algorithm is verified on a 70-bus system, and the influence of distributed PV output and different regulation strategies on the hosting capacity of flexible distribution network is analyzed.