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水力发电学报 ›› 2020, Vol. 39 ›› Issue (7): 61-72.doi: 10.11660/slfdxb.20200707

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三峡水库蓄水时机群决策方法研究

  

  • 出版日期:2020-07-25 发布日期:2020-07-25

Group decision study on Three Gorges reservoir's water impounding schemes

  • Online:2020-07-25 Published:2020-07-25

摘要: 汛末提前蓄水能在风险可控的条件下提高水库蓄满率,增益良多。目前针对三峡水库汛末蓄水时机的研究很多,但侧重点不同,且最佳蓄水时机的选取缺少决策技术支持。为了将现有研究成果有效整合,供上级决策者参考,提出了专家群体最大满意度群决策模型。首先,各专家运用累积前景理论对蓄水时间方案进行排序,然后以专家群体满意度最大为目标,求解使专家群体满意度最大的群决策结果。结果显示,9月11日蓄水的方案可以在较小的风险条件下取得较大效益,为最优方案,该结果与传统决策方法结果相同,表明了所提群决策模型的有效性。此外,该模型充分考虑专家决策心理,尊重群体意见,结果有据可循,能为研究三峡汛末蓄水时机问题提供一种新的有效手段。

关键词: 三峡水库, 蓄水时机, 专家满意度, 前景理论, 群决策

Abstract: Early impoundment at the end of flood season can improve the full storage rate of reservoirs at controllable risk and create significant benefits. Extensive studies have been conducted on the Three Gorges reservoir's operation schemes of water impounding at the end of flood season, but their focuses are quite different and they lack the support of decision-making technology in selecting water impounding schemes. This paper presents a group decision-making model of experts’ most-satisfaction to integrate the existing research fruits on the reservoir's impounding schemes for higher level decision making. We rank the available schemes using the method of cumulative prospect theory and the matrices of experts' decision, and then solve the model to maximize the satisfaction of the expert group. The results show that the best scheme is to start impoundment on September 11 and this can achieve greater benefits with a lower risk and agrees with the result of the traditional decision method, verifying the effectiveness of our group decision model. This model has fully considered experts' decision-making psychology and respects the group opinions of experts; thus it gives evaluation results that can be followed and provides a new effective approach to the reservoir's operation schemes of early water impounding.

Key words: Three Gorges reservoir, water impounding time, experts' satisfaction, prospect theory, group decision-making

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