D-Vine Copula Based Spatial Correlation Characterization for Capacity Credit Assessment of Wind and PV Power
摘要
As the share of renewable energy in the power system increases, the risk of inadequate load supply also rises. Therefore, the concept of capacity credit (CC) is introduced to reflect the power supply capability of generation resources in the field of power planning. Accurate assessment of CC relies on reasonable reconstruction of wind and photovoltaic (PV) power output scenarios. In this paper, a method for modeling the spatial correlation of output from multiple wind farms and photovoltaic power stations based on D-vine copula is proposed. Moreover, an efficient interpolation method for CC assessment using D-vine copula sampling is introduced. Numerical experiments are designed based on two wind farms and two photovoltaic power stations in a real power system in China, demonstrating the effectiveness and superiority of the proposed model. Furthermore, we analyzes various factors that influence combined CC of wind and PV power.
