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水力发电学报 ›› 2019, Vol. 38 ›› Issue (10): 47-58.doi: 10.11660/slfdxb.20191005

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基于结构方程模型的水库多目标互馈关系研究

  

  • 出版日期:2019-10-25 发布日期:2019-10-25

Study on multi-objective mutual feedback relationships of reservoirs based on structural equation modeling

  • Online:2019-10-25 Published:2019-10-25

摘要: 梯级水库多目标问题涉及的因子集维度较高,目标间关系错综复杂,传统统计学方法难以同时考虑各目标所涉及的不同指标,对于互馈关系仅可给出定性分析。针对此问题,本文建立梯级水库发电-供水-生态多目标优化调度模型,采用快速非支配排序遗传算法(NSGA-Ⅱ)求解,并提出三者间互馈关系的初步假设,进而引入结构方程模型(SEM),以非劣解集内各指标值作为输入数据,进行高维验证性因子分析,针对目标间互馈关系给出可视化、定量化的计算结果。溪洛渡-向家坝梯级水库的研究结果表明,在丰、平、枯不同典型年中发电-供水的冲突最剧烈,其次为发电-生态,而供水-生态的互馈关系并不显著;另外,随着天然来流由丰变枯,发电-供水矛盾急剧锐化。

关键词: 结构方程模型, 梯级水库, 多目标优化调度, 互馈关系

Abstract: The multi-objective optimization problem of cascade reservoirs involves high factor dimensions and complicated inter-objective relationships. Traditional statistical methods are difficult to consider the target information contained in different indicators comprehensively, and can give only qualitative analysis of their mutual feedback relationships. Aiming at the problem, this paper constructs a power generation-water supply-ecology multi-objective optimal scheduling model for cascade reservoirs, solves it using a fast non-dominated sorting genetic algorithm (NSGA-Ⅱ), and formulates a preliminary hypothesis of mutual feedback relationships among the three objectives. And we apply a structural equation modeling (SEM), conduct a high-dimensional confirmatory factor analysis using the index values given by the multi-objective non-inferior solution set of cascade reservoirs, and present visual and quantitative calculation results for the mutual feedback relationships among the objectives. The results of the Xiluodu-Xiangjiaba cascade reservoirs show that under different inflow frequencies, the power generation-water supply conflict is the most severe, followed by power generation-ecology; while compared with these conflicts, the water supply-ecology feedback relationship is insignificant. As the frequency of inflow increases, the conflict between power generation and water supply sharpens rapidly.

Key words: structural equation modeling, cascade reservoirs, multi-objective optimal scheduling, mutual feedback relationship

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