Multi-objective integrated decision method of cascade hydropower stations based on optimization algorithm and evaluation model

Abstract

The establishment and functioning of cascade hydropower stations have significantly altered the natural state of rivers, leading to increasingly severe ecological impacts downstream. To mitigate the adverse effects of cascade reservoir impoundment on river ecosystems and achieve the multi-objective goals of hydropower development and environment protection, this study presents an integrated decision model for optimizing the operation of cascade hydropower stations, utilizing the lower Jinsha River as a case illustration. The proposed model comprises three main components: ecological flow calculation, establishment of a multi-objective optimization model, and scheme evaluation. The ecological flow threshold for the river was determined using the Tennant method. The multi-objective optimization model was formulated with objectives including power generation, ecological flow shortage, and navigation disruption days. The NSGA-II algorithm was employed to resolve the optimization framework. The improved TOPSIS method was adopted for evaluating the operation schemes. The case study conducted in the downstream region of the Jinsha River revealed significant conflicts between the objectives of power generation and ecological conservation. Moreover, different typical years exerted a considerable influence on determining the optimal operation scheme. The proposed integrated decision model provides a scientific framework for guiding the water resource dispatching of cascade hydropower stations and achieving the harmonization of economic and ecological benefits. Overall, this research contributes to the academic field by addressing the complex difficulties related to optimizing the operation of cascade hydropower stations while considering ecological concerns. The findings underscore the importance of adopting a comprehensive decision-making approach that integrates multiple objectives and utilizes advanced algorithms for sustainable river management.