Multi-Objective Scheduling Model for Cascade Hydropower Stations Based on Comprehensive Unit Condition Evaluation

Against the backdrop of current energy shortages and the emphasis on environmental sustainability, cascade hydropower stations play a crucial role in the energy sector as a clean and renewable energy source. This study focuses on a multi-objective scheduling model for cascade hydropower stations based on comprehensive unit condition evaluation, aimed at enhancing the optimization efficiency of cascade hydropower station scheduling. We have constructed a scheduling model with the objective functions of minimizing the total residual load and peak-valley difference. This model is designed to satisfy various constraints, including the output, electricity generation, water balance, reservoir capacity, spillage, and the on-off duration of hydroelectric units. Following the determination of unit start-stop priorities, we employed the Levy Flight Search Mechanism (LFSM) and an improved differential evolution algorithm with pollen dispersal for model resolution, obtaining optimal scheduling results for cascade hydropower stations. Experimental results indicate that the model, through comprehensive evaluation of the operational states of hydroelectric units, has significantly improved the selection of participating units in the scheduling process, resulting in a notable increase in unit output post-optimization. The fluctuation in the residual load curve is decreased by about 50%, compared with the original load.