Optimal Configuration of Long-term and Short-term Energy Storage Based on Improved Generative Adversarial Network Scenarios

The increasing proportion of renewable energy sources poses new demands on the flexibility regulation capability of the new power system. To address this issue, this paper proposes a long-short term energy storage optimization method that guarantees multi-timescale flexibility regulation capability of the system through dual regulation of short-term power and long-term energy. First, a wind-solar joint output scenario generation method based on an improved generative adversarial network is proposed, which accurately characterizes the boundary of wind-solar output by adding month label information. Second, considering the technical characteristics of different types of energy storage, a long-short term energy storage operation coordination strategy is proposed. Finally, a dual optimization model of long-short term energy storage configuration that considers both economic and flexibility objectives is established. The optimal energy storage configuration plan is obtained through continuous optimization and iteration of the upper and lower level models. The proposed method is validated on the improved IEEE-RTS 24-node system, and the results demonstrate that the proposed method can effectively improve the flexibility and economic performance of high-penetration power systems.