Benefits evaluation method for short-term scheduling of cascade hydropower station group in historical data-scarce regions

In remote and underdeveloped areas of China, poor management, coupled with limited financial and human resources, has led to the widespread loss of historical hydrological data for many small basins and hydropower stations (HSs). The absence of historical data prevents HS owners from optimizing scheduling strategies to maximize their operational efficiency and financial benefits. To address this issue, this study proposes the H-RLC (Hydropower Runoff Recovery, Load Curve Configuration, and Cost Optimization) Method, a short-term scheduling benefits evaluation approach for HSs in data-scarce regions. The method consists of: (1) a runoff data recovery method for reservoir-type HSs based on historical power output; (2) a load curve reconfiguration method that incorporates load trends and time-of-use (TOU) tariff patterns; and (3) a minimum electricity cost model that integrates TOU and capacity tariffs for evaluating scheduling benefits. The proposed model was applied to evaluate the scheduling benefits of a HSs enterprise in China. The simulation results indicate that the total electricity costs were reduced by 3.8 % over five years, translating to savings of 0.018¥/kWh. These findings provide enterprises with greater confidence in achieving energy savings and efficiency improvements through the rational scheduling of ‘self-owned’ HSs, whose power generation plans are independently managed.