董增川, 倪效宽, 陈牧风, 姚弘祎. 流域水资源调度多目标时变偏好决策方法及应用[J]. 水科学进展, 2021, 32(3): 376-386. DOI: 10.14042/j.cnki.32.1309.2021.03.006
引用本文: 董增川, 倪效宽, 陈牧风, 姚弘祎. 流域水资源调度多目标时变偏好决策方法及应用[J]. 水科学进展, 2021, 32(3): 376-386. DOI: 10.14042/j.cnki.32.1309.2021.03.006
DONG Zengchuan, NI Xiaokuan, CHEN Mufeng, YAO Hongyi. Multi-objective time-varying preference decision-making method for basin water resource dispatch and its application[J]. Advances in Water Science, 2021, 32(3): 376-386. DOI: 10.14042/j.cnki.32.1309.2021.03.006
Citation: DONG Zengchuan, NI Xiaokuan, CHEN Mufeng, YAO Hongyi. Multi-objective time-varying preference decision-making method for basin water resource dispatch and its application[J]. Advances in Water Science, 2021, 32(3): 376-386. DOI: 10.14042/j.cnki.32.1309.2021.03.006

流域水资源调度多目标时变偏好决策方法及应用

Multi-objective time-varying preference decision-making method for basin water resource dispatch and its application

  • 摘要: 传统多目标决策方法难以刻画流域水资源系统调度周期内多目标互馈关系及需求动态变化, 可能导致关键时期特定目标保障不足。为弥补该缺陷, 提出多目标时变偏好决策方法。以金沙江下游为例, 分析发电与生态目标需求的时空变异性, 构建并求解两目标随时程变化的Pareto前沿簇, 量化各时期目标间竞争强度, 基于灵敏比的非支配关系, 定量识别各调度时期决策人的目标偏好, 形成偏向度决策支持集, 建立多目标时变决策模型。结果表明: 考虑时变偏好的决策方法, 其动态累积Pareto前沿可以支配传统静态Pareto前沿; 相较于传统方法, 研究区全年增发电量0.7亿kW·h, 全年和关键生态期生态效益分别提升8.06%和2.83%, 可以在保持发电效益的同时显著优化生态效益, 并提高关键时期生态需求的保障程度。

     

    Abstract: In view of the dynamic change of competition relationship and its intensity among multiple objectives in different periods of basin water resources system scheduling process, a multi-objective time-varying-preference decision-making method is proposed. Taking the lower reaches of Jinshajiang River as an example, the spatiotemporal variabilities of power generation and ecological objectives are analyzed, and the Pareto frontier cluster of these two targets in chronological order is constructed and calculated. In addition, based on the non-dominated relationship of sensitivity ratio between targets, the objective preference of decision makers in each scheduling period is identified quantitatively to form the decision support set of bias degree, and a multi-objective time-varying decision-making model is established. The results show that there is a significant competitive relationship between cascade power generation and ecological objectives in the lower reaches of Jinshajiang River in normal flow year. The competition is the strongest in the refill period and weakest in the flood season; the competition intensity strengthens with the increase of power generation in each period. The time-varying-preference decision-making method, based on the physical basis of dynamic Pareto front, can significantly optimize the ecological benefits while maintaining the power generation benefits, and improve the guarantee degree of ecological demand in the critical period.

     

/

返回文章
返回