Abstract:

The integration of a high proportion of wind and solar energy into the power grid poses challenges for grid peak regulation owing to the inherent volatility of these renewable energy sources. However, energy storage systems, with their bidirectional charging and discharging capabilities, offer an excellent solution for peak regulation. Therefore, addressing the dynamic peak regulation capacity of energy storage to accommodate wind and solar fluctuations has become a critical issue in developing the new power system. To tackle this challenge, a collaborative low-carbon economic dispatch model combining wind, solar, thermal power, and energy storage has been proposed. This helps energy storage systems to adapt to the volatility of these energy sources. First, the output distribution function and active output scenarios were developed using the optimal Copula joint probability method. This modeling provides a strong foundation for enabling energy storage systems to adapt to the volatility of wind and solar energy. Second, the peak shaving cost function, the wind and solar power curtailment cost function, the dynamic peak shaving cost function of energy storage, and the operating costs of thermal power units were defined. These were integrated into a joint optimization objective function, accompanied by a set of constraint conditions. Third, a revised particle swarm optimization algorithm was employed to efficiently solve the joint optimization objective function. Finally, a practical example was used to simulate and validate the proposed algorithm. The results demonstrated that the low-carbon economic dispatch method significantly improves the power grid's peak shaving capacity and economic performance, while reducing wind and solar power curtailment.

Key words: dual carbon, wind and solar new energy, energy storage, peak shaving, economic dispatch