Short term hydropower scheduling considering cumulative forecasting deviation of wind and photovoltaic power

The cumulative forecasting errors of wind and photovoltaic (PV) power pose serious challenges to the short-term scheduling of hydropower stations that connected to the same regional power grid. The variable and intermittent nature of wind and PV power necessitate a flexible power source to achieve power balance. Consequently, hydropower, with its flexible adjustment capability, plays a crucial role in supporting the consumption of wind and PV power stations in short-term scheduling. Meanwhile, to address the grid's peak shaving requirement, the scheduling of cascaded hydropower system becomes increasingly complex. Given the limitations of current wind and PV power output prediction technologies, achieving precise forecast remains challenging. In practice, the actual outputs of wind and PV power stations often diverge considerably from predicted values over multiple consecutive periods. This variability may result in the underutilization of wind and PV power if the reserve capacity of hydropower stations is insufficient. Therefore, it is essential to account for the cumulative deviation in electricity from wind and PV sources. By computing probability distribution and establishing boundary condition of the cumulative deviation, the operation of the cascaded hydropower system can be controlled more effectively, thus enhancing the stability of a multi-energy complementary system. This study employs Gaussian Mixture Model (GMM) to characterize the probability distributions of cumulative electricity deviation across multiple periods of wind and PV power and takes it as restriction to regulate the operation of hydropower stations. In order to balance the deviation electricity, the downward electricity reserve, upward electricity reserve and the storage energy of the cascaded reservoirs are introduced as restrictive conditions. The proposed Hydro-wind-PV peak shaving model is then applied to the short-term optimal scheduling of the Lancang River cascaded hydropower system to validate the feasibility and efficacy.