Optimal scheduling of a cascade hydro-thermal-wind power system integrating data centers and considering the spatiotemporal asynchronous transfer of energy resources

The cooperative power generation of cascade hydropower stations and balanced power consumption of data centers can promote power flow optimization. However, the asynchrony of the water flow and the spatiotemporal transfer time of data loads brings great challenges to the power system. To address this problem, a power system scheduling strategy which considers the spatiotemporal asynchronous transfer characteristics of multivariate energy is proposed in this paper. Firstly, an operational model of a cascade hydropower station is established which considers the demand of sand flushing and navigation. Secondly, a collaborative scheduling method with multiple data centers is designed which considers the spatiotemporal transfer of data loads, and a reserve model with a cascade effect is constructed which is controllable through data centers. Furthermore, an optimal operational model of a cascade hydro-thermal-wind power system is established which considers data centers participating in scheduling and aims to minimize the operational cost of the power system while meeting the power load. Additionally, the optimization model is converted into a standard mixed-integer linearization programming (MILP) problem using a linearization technique. The IEEE-RTS79 system simulation results show that the operational cost of the power system is reduced by 16.14 %.