Collaborative planning of wind power, photovoltaic, and energy storage for new power system based on Copula scenario generation

In order to promote the consumption of renewable energy into new power systems and maximize the complementary benefits of wind power (WP), photovoltaic (PV), and energy storage (ES), studying a collaborative planning of wind, PV and energy storage systems is of significant importance. This paper first considers the seasonality, uncertainty, and correlation of WP and PV outputs, generating joint output scenarios reflecting the correlation between WP and PV power based on Copula functions. These scenarios are reduced to typical operating scenarios using the simultaneous backward reduction (SBR) algorithm. Secondly, a multi-objective planning model is established, considering both the economy and the environmental sustainability of the system. The model is converted into a single-objective problem using the analytic hierarchy process (AHP), and a carbon reduction benefit evaluation index is established. Finally, a case study of a power supply area in Wenzhou was conducted to validate the effectiveness of the proposed planning method. Compared to planning models that do not consider wind and PV power correlation, the proposed planning method reduces the system's annual investment and operating costs by 90.56527 million yuan, increases carbon reduction benefits by 89.79 thousand tons, and improves the annual renewable energy absorption rate by 0.64%.