High-temperature reservoir thermal energy storage (RTES) represents a promising approach to storing surplus renewable energy and waste heat in subsurface formations for later recovery, offering a reliable pathway toward enhanced grid stability. To store heat using high-temperature fluid, deep reservoirs with depths greater than 2 km are required for minimal heat loss. However, the mechanism controlling the efficiency of RTES and its value on grid stability remain unclear due to a lack of research and field demonstrations. To reveal this mechanism and achieve optimal heat storage performance for quantifiable grid stability improvement, this study presents an in-depth numerical analysis of the thermal behavior and storage performance of an open-loop RTES system. The effects of critical factors on the system’s performance are analyzed, including the injection temperatures during heat storage and production, injection rates, storage and production schedule. Results show that a higher injection temperature during storage with a lower one during production yields the highest heat recovery. A higher hot fluid injection rate for storage and a lower cold fluid injection rate for production results in the lowest thermal drawdown during production, which is the most beneficial for power generation. To achieve both high production temperature and thermal power, a balanced combination of longer duration storage and production is recommended. Building on these findings, a power system modeling framework based on linearized AC optimal power flow (LPAC) is developed to represent the joint operation of RTES and the power grid. RTES simulation outputs are incorporated as input parameters in the LPAC model, influencing generation dispatch and allowing evaluation of grid stability under stressed operating conditions. Results indicate that RTES, with stronger heat production performance, provide greater grid stability benefits. This framework offers a structured and quantifiable approach to evaluate the operational benefits of RTES, with analysis indicating improvements in grid stability and reliability during stressed conditions.

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