The energy, water supply, and ecology coordination for middle-long-term reservoirs scheduling with different connection modes using an elite mutation strategy-based NMOSFLA. Issue 6 (21st October 2022) - Yang, Zhe; Wang, Yufeng; Yang, Kan; Hu, Hu; Song, Songbai; Xu, Shiqin; Zhang, Xuguang; Ye, Sumeng; Li, Jiaxin
Abstract: Conventional reservoir operation emphasizes power generation (PG) with ignoring downstream river ecosystem and water supply benefits for sustainable development. Compared with the model defining water supply and ecological flow requirements as constraints, a novel long-term multi-objective scheduling model in complex parallel reservoir system (LTMOSCPRS) is developed to assess and achieve win–win and sustainable development for energy, water supply, and ecological benefits. The suitable and ideal ecological water requirements are calculated based on the requirement level index. Afterward, the novel multi-objective shuffled frog leaping algorithm (NMOSFLA) including renewed frog grouping, local search, and external elite frog set mutation strategies is proposed. Results indicate that three optimization objectives expose a mutual competing relationship. The benefit of the river ecosystem will increase at a loss of PG and water supply guarantee rate (WSGR). Therefore, the parallel reservoir system should be adjusted to improve the benefits of WSGR and ecological water spill and shortage (EWSS) with minimizing the loss of PG, simultaneously. Finally, the NMOSFLA is verified to outperform other compared methods at the solution diversity and convergence which is evaluated by multiple indicators. Overall, the NMOSFLA provides efficient reservoir operation schemes for decision-makers to select optimal trade-off schemes and feasible ways to solve the LTMOSCPRS. HIGHLIGHTS: Propose a novel multi-objective shuffled frog leaping algorithm (NMOSFLA) based on multiple improvement strategies. Adopt the NMOSFLA to efficiently solve long-term multi-objective scheduling of complex reservoir systems. Calculate the suitable and ideal ecological water requirements based on the requirement level index (RLI). Verify that the NMOSFLA outperforms other methods on the solution diversity and convergence.