Integrated multi-time scale sustainable scheduling of wind power incorporating combined high energy demand and energy storage

Effective wind power utilization relies on high-energy load systems with exceptional flexibility and substantial power capacity for efficient energy regulation. This research presents a pioneering multi-time scale sustainable scheduling model designed to address the substantial wind power consumption challenge faced in Northwest China. The model considers the joint participation of high-energy load and energy storage in wind power consumption. Initially, the mechanism of high-energy load in accommodating surplus wind power is analyzed, and models for discrete and continuously adjustable high-energy loads are developed. Subsequently, a multi-time scale optimization model is proposed, considering the coordination of battery energy storage devices and high-energy load demand response. In the day-ahead stage, minimizing wind curtailment is the optimization objective, achieved by guiding high-energy loads to respond to wind power changes. In the intraday stage, following the day-ahead plan, the objective is to minimize the deviation between the wind power generation and the forecasted actual intraday wind power generation, further reducing the impact of power fluctuations through multi-time scale rolling optimization. Finally, a case study is constructed based on representative off-peak days in Northwest China. Simulation analysis shows that compared to traditional scheduling methods, the proposed strategy can effectively improve the wind power consumption capacity and reduce wind curtailment by 7.41 %. The proposed scheduling strategy can effectively increase the level of wind power consumption in the system, providing key insights and important guidance for the sustainable development of wind energy in the future.