Research on Peak-Shaving Joint Optimal Dispatch of Multi-Energy Complementary System with Hybrid Pumped Storage Hydropower Plant

Wind and photovoltaic power have become vital components in the transformation of energy structures. However, their inherent features of intermittency, fluctuations, and randomness severely constrain large-scale grid integration and efficient utilization. To address this challenge, we conduct a dayahead peak-shaving joint optimal dispatch study for the Hydro-Wind-PV Complementary System. By comprehensively considering grid-side stability requirements and the complex operational constraints of the complementary system, a day-ahead joint optimization dispatch model is established to minimize the variance of residual load. Accounting for uncertainties in forecasts, typical dispatch scenarios are constructed as model inputs based on hydrological conditions and weather patterns. The Improved Moth-Flame Optimization Algorithm is ultimately applied to achieve efficient problem-solving. Experimental results demonstrate that the proposed methodology fully leverages the peak-shaving capacity of the Hybrid Pumped Storage Hydropower Plant, effectively reduces the peak-valley difference in grid residual load, and provides decision support for scheduling plan formulation in the complementary system within new-type energy systems.