Optimal Peak-Shaving Dispatching of Hydropower Station in Response to Long-Term Load Demand of Power Grid

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Hydropower stations play a crucial role in meeting the demand for peak shaving in the power grid. A method called the adaptive segmented cutting load algorithm (ASCLA) is proposed to address the problem of the uneven distribution of regulation effects when formulating long-term peak-shaving dispatching plans for hydropower stations. This method mainly consists of three components: full-period load segmentation, sub-period end water level treatment, and staged cutting load optimization. It can improve the average regulation ability of hydropower stations for the power grid’s long-term load by combining the inflow conditions. In order to compare the progressiveness of the proposed method, the Three Gorges hydropower station and the Central China Power Grid were used as research objects, and its long-term peak-shaving performance was analyzed by comparing it with that of the classical HCL solution method. The simulation dispatching results show that the proposed method resulted in significantly improved peak-shaving indicators, such as the mean squared deviation of the rolling window, load fluctuation index, and peak value compared to HCL. In years with abundant reservoir runoff, the comprehensive improvement can reach about 25%, indicating that the proposed ASCLA has more advantages in responding to the long-term load regulation needs of the power grid compared to existing methods. The research results of this paper can provide a reference and guidance for peak-shaving dispatching in hydropower stations during the dry season, effectively improving the long-term peak-shaving benefits of hydropower stations.