Balancing Ecological Requirements and Power Generation in Reservoir Operation in Fish Spawning Seasons

Abstract

Various studies have demonstrated that the long-term flow regime plays an important role in stimulating fish spawning. The flow regime is altered by the construction and operation of reservoirs. In this study, a flow-regime identification method is proposed, which extracts the rising hydrograph processes with a certain amplitude and duration through multiple passes of denoising and filtering algorithms to filter out random fluctuations with different amplitudes. The identified rising hydrograph processes were then quantitatively characterized using three parameters. A multiobjective optimization model was constructed to mimic the natural flow process in reservoir discharge and to maximize the output value of the power plant using the Nondominated Sorting Genetic Algorithm (NSGA-II). Finally, the proposed model was applied to the planning of a large-scale reservoir on the upper reaches of the Yellow River in China. The derived Pareto front in different hydrological years was analyzed using the analytic hierarchy process (AHP) method, and various operational schemes were evaluated on this basis.