Abstract: Unit load dispatch optimization for hydropower stations is critical to improving their operational efficiency and economic performance. Traditional single-objective optimization methods have struggled in the balance between economic performance and operational safety. This paper constructs an optimization model that has two objectives－to minimize water consumption of a hydropower station and reduce the number of times its units cross into the vibration zone. The Multi-Objective Grey Wolf Optimization (MOGWO) algorithm is beneficial for optimizing the load dispatch of the units, based on the in-situ data collected from the Yanguoxia hydropower station. Generally, the MOGWO algorithm demonstrates superior overall performance in solving a multi-objective optimization problem, compared to classical multi-objective optimization algorithms－such as the Non-dominated Sorting Genetic Algorithm II (NSGA-II), Decomposition-based Multi-objective Evolutionary Algorithm (MOEA/D), and Multi-Objective Particle Swarm Optimization (MOPSO). Simulation results indicate that MOGWO effectively reduces the units’ water consumption rate by 9.7%, and significantly lowers the vibration zone-crossing frequency. The efficient and stable solution proposed in this paper contributes to the effective resolution of multi-objective optimization problems in hydropower unit operation.

Key words: hydroelectric generating units, load allocation, vibration zone, Pareto optimality, grey wolf optimizer, multi-objective optimization