水力发电学报2025，Vol.44Issue(12)：52-64,13.DOI:10.11660/slfdxb.20251205
多目标灰狼优化算法在水电机组负荷分配中的应用研究
Application of multi-objective grey wolf optimization algorithm to load dispatch of hydropower units
摘要
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.关键词
水电机组/负荷分配/振动区/Pareto最优/灰狼优化/多目标优化Key words
hydroelectric generating units/load allocation/vibration zone/Pareto optimality/grey wolf optimizer/multi-objective optimization分类
建筑与水利引用本文复制引用
YU Huiqun,YAO Yuchen,QIU Yaming..多目标灰狼优化算法在水电机组负荷分配中的应用研究[J].水力发电学报,2025,44(12):52-64,13.基金项目
国家电力投资集团有限公司科技项目(KYTC2021SD04) （KYTC2021SD04）
