Abstract: A multi-objective coordinated optimal scheduling model is developed for the day-ahead operation of a hybrid pumped storage-water transfer coupled system that is faced with scheduling difficulty involving how to coordinate power generation, water supply, and water transfer. It uses a multi-objective sparrow search algorithm to generate a Pareto-optimal solution set. We compare its optimization results with those of a rule-based load allocation benchmark in a case study of the Hunanzhen-Huangtankou-Wuxijiang hybrid pumped storage system. The results indicate that scheduling such a coupled system must consider significant trade-offs among the objectives－a competitive relationship of power generation versus water supply and water transfer, and an overall compatibility of water supply and water transfer. The Pareto solutions generated using this new model achieve simultaneous improvement on all the three objectives－power generation, water supply reliability, and transferred water volume－in comparison with the benchmark scheme. For a typical dry-season day, power generation increases by 55.2 MW·h, water supply reliability improves by 7.50%, and transferred water volume increases by 11,700 m3. Our scheduling model proves effective and useful for the coordinated operation of water and power networks.

Key words: reservoir operation, cascade reservoirs, hybrid pumped storage power station, multi-objective optimization, inter-basin water transfer, day-ahead scheduling