Ecological reservoir operation based on DFM and improved PA-DDS algorithm: A case study in Jinsha river, China

This study aims to explore the optimization of reservoir operation in the Jinsha River, accounting for both economic and ecological needs. Power generation was set as an objective to express economic needs, while water supply, shipping, and flood control were considered as restrictions. The distribution flow method (DFM) based on Pearson-III curve was proposed to calculate the most optimal ecological flow (MOEF). Additionally, minimal difference between the outflow and MOEF was set as an objective to reflect ecological needs. Results indicated that the DFM was more objective, effective, and convenient than the improved Tennant method and monthly frequency computation method in calculating the MOEF. An improved Pareto archived dynamically dimensioned search (PA-DDS) algorithm was introduced to address completed reservoir optimization. Results highlighted that the application of the improved PA-DDS produced more convergence, uniformity, and stability in nondominated solutions (NDS), compared with the non-dominated sorting genetic algorithm-II (NSGA-II). Separate optimization and joint optimization of cascade reservoir operation were studied using the improved PA-DDS. The results indicated that joint optimization produced higher power generation in the dry year and normal year, and significant reduction in the difference between the outflow and MOEF in the wet year.