Short-term peak-shaving model for hydro-wind-photovoltaic hybrid system coupled with complex ecological constraints

ABSTRACT Hydropower's critical role in stabilizing grids with high variable renewable energy (VRE) penetration is counterbalanced by ecological risks. Discharge fluctuations from hydropower peaking operations – driven by wind and solar intermittency, imposing physiological stress on aquatic biota dependent on stable hydrological regimes. Modeling challenges include inconsistent ecological flow requirements for cascaded systems, incorporating complex ecological constraints, and solving inefficiencies. To address this, we developed a hydro-wind-photovoltaic short-term optimal dispatch model balancing peaking performance with ecological sustainability. First, ecological constraints at different stations were categorized into three classes (I, II, III) based on flow limits and control methods, targeting varied ecological needs. Second, we proposed a short-term joint peak dispatching model coupled with these constraints, optimizing hydropower peak capacity while meeting ecological demands. Finally, the big M method transformed nonlinear ecological constraints into a solvable MILP algorithm, reducing complexity and improving efficiency. A case study on six Wujiang River cascade reservoirs demonstrated the model: solution efficiency improved by 45.6% versus DPSA, alongside a 69% reduction in peak-to-valley differences. Comparing constraint classes revealed Class I as the most stringent, followed by III and II. The model underscores the necessity of sound ecological flow design in hydropower projects and improves constraint logic consistency.