模拟季节性热储能的季节性动态在可再生能源系统全年调度中的应用

Abstract Seasonal thermal storage (STS) enables the long-term storage of renewable energy in heat, which could effectively address the seasonal mismatch between renewable energy supply and heat demand. This paper models the temperature distribution of the water-based STS, considering the insulating effects of the soil surrounding the tank. Considering that the commonly used state-of-charge (SOC) model could not describe the time-variant heat loss in detail in a renewable energy system scheduling problem, a temperature field correction method is proposed to correct the scheduling results. Three case studies are performed on Garver’s 6-node system and HRP-38 system to validate the proposed method’s enhanced accuracy in managing STS compared to the SOC model. The proposed method could also reduce renewable curtailment in the scheduling problem due to a more detailed description of the heat loss process and a more effective renewable energy system scheduling scheme.