Multi-Time Scale Optimization Scheduling Model for Over-Matched PV Station with Energy Storage

With the increasing PV installed capacity, some PV stations are experiencing overcapacity, where the installed capacity of PV exceeds the limit of the transformer, resulting in large curtailment of PV generation. Therefore, this paper proposes a multi-time scale optimization scheduling method for over-matched PV station with energy storage. Firstly, based on the multi-variate normal Copula method, the time autocorrelation of PV power and the conditional correlation with prediction are extracted Secondly, to enhance the stability of power generation while increasing the revenue of PV station, a multi-time scale optimization scheduling strategy is proposed. The day- ahead joint output of PV and energy storage has been kept as stable as possible, while the intra-day power generation plan is dynamic updated to address prediction deviations and real-time operation scheme is applied to track intraday plan curve. Finally, the effectiveness of the proposed method is verified based on a PV station in China.