Intelligent optimization method for time period of power grid operation based on knowledge model

Modern power systems impose higher requirements on the time period selection of power grid operation. On one hand, factors influencing operating costs have become more intricate, and on the other hand, the disparities in costs across different time periods have become more pronounced. Therefore, based on a knowledge model, this paper proposes a method to determine the optimal time period for operations. Firstly, this paper analyzes various factors that affect the operation cost and provides a quantitative calculation model. Then, to accelerate the optimization process, a knowledge model for optimizing the operation time period is established based on historical operating data, especially operation ticket data. Finally, the proposed optimization method is applied to the power grid in northwest China. The results demonstrate that the proposed method can identify the optimal operational time period and has a higher computational efficiency compared to the traditional enumeration method.