Short-Term Hydro-Wind-PV peak shaving scheduling using approximate hydropower output characters

With the massive construction of wind and photovoltaic (PV) power plants, the uncertainty of their output poses challenges for grid peak regulation. Hydropower, characterized by convenient regulation, fast response speed, and low cost, is an ideal choice for compensating for wind and PV energy generation. Mixed-Integer Linear Programming (MILP) is employed to work out short-term scheduling of hydro-wind-PV power. However, considering hydropower scheduling alone is already highly complex, and incorporating the deviations in wind and PV energy further reduces the solution efficiency. In practical scheduling, operators often rely on empirical scheduling methods that can yield satisfactory results. To enhance solution quality and improve the scalability and efficiency of the MILP method, a short-term optimization scheduling model for hydropower plants has been proposed and applied to the Hongshui River cascade system. The case study shows that the model can perform calculations in just 2 s, demonstrating extremely high computational efficiency. This can significantly enhance decision-making in cascaded hydropower scheduling. At the same time, the model leaves sufficient reserve capacity to address the uncertainty of wind and solar power output while reducing the residual load by 0.8 %, which is beneficial for the stable operation of the grid.