A PV Hosting Capacity Evaluation Method Considering Source-Load Correlation

Nowadays, owing to the excessive integration of photovoltaic (PV) in distribution network, the system is facing several security problems, thus, it is urgent to accurately evaluate the PV hosting capacity of the system. This paper proposes a PV hosting capacity evaluation method considering the scenario generation. The Gaussian mixture model and Copula theory are adopted in combine with the Monte Carlo sampling as well as the clustering method to generate the typical daily scenarios for the evaluation of the hosting capacity. Furthermore, a successive second-order cone programming (SOCP) method incorporating additional linearized constraints is proposed to reduce the relaxation gap result from the use of the SOCP method in PV hosting capacity problem and obtain the optimal solution of the original problem through multiple iterations. Simulations are performed on an IEEE-33 bus system integrated with PV systems to demonstrate the effectiveness of the proposed method.