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| 考虑受水区需水时空不确定的调水工程水量调度与滚动优化研究 |
| Research on Regulation and Rolling Optimization of Water Transfer Projects Considering the Uncertainty of Spatiotemporal Water Demand in Water Receiving Areas |
| 投稿时间：2024-12-10 修订日期：2025-10-15 |
| DOI： |
| 中文关键词: 调水工程 水量调度 滚动优化研究 需水不确定性 |
| 英文关键词: Water transfer project Water regulation Rolling Optimization Uncertainty of spatiotemporal water demand |
| 基金项目:国家自然科学基金（52394234）；重点研发课题（2022YFC3204603）；水利部重大科技项目 (SKS-2022117) |
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| 中文摘要: |
| 对调水工程受水区需水的准确描述及实时更新能使调度方案适应复杂的需水变化，从而增强对特殊气候年份的适用能力。本研究以胶东调水工程为例，进行了需水不确定下的水量调度与滚动优化研究。首先对受水区需水时空不确定性进行了分析描述。时间变化层面，在历史时刻、年度调度方案制定时与一段调度期后三个时刻，分别采用数据挖掘模型（DDM）、机会约束规划（CCP）与滚动优化技术，按照定性分析-定量分布函数分析-滚动修正的技术链条，对受水区需水的时变性进行分析。空间变化层面，采用主成分-层次分析（PCA-AHP）需水量计算法，将各市尺度需水细分为县尺度需水。然后以受水区总缺水最小为目标，构建了年度水量优化调度模型与滚动优化调度模型，并采用迭代求解法进行模型计算。最后对调度方案进行了可变模糊评价，所得调度方案能缓解受水区严峻的缺水情况，适应复杂的需水变化，符合工程实际调度过程。 |
| 英文摘要: |
| Accurate depiction and real-time updates of water demand in the receiving area of water transfer projects can enable the regulation scheme to adapt to complex changes in water demand, thereby enhancing its capacity to cope with special climatic years. This study takes the Jiaodong Water Transfer Project as a case study to conduct regulation and rolling optimization under uncertain water demand. Firstly, the spatiotemporal uncertainty of water demand in the receiving area was analyzed and described. At the level of temporal variation, data mining models (DDM), chance-constrained programming (CCP), and rolling optimization techniques were applied at three moments: historical condition, during the formation of annual regulation scheme, and after a regulation period, by the technical chain of qualitative analysis-quantitative distribution function analysis-rolling correction. At the level of spatial variation, the principal component analysis-artificial hierarchy process (PCA-AHP) water demand calculation method was used to refine water demand from the city level to the county level. Then, with the goal of minimizing the total water shortage in the receiving area, annual optimization regulation model and rolling optimization regulation model were constructed, and iterative solution method was used for model calculation. Finally, variable fuzzy evaluation was conducted on the regulation schemes. The optimal schemes effectively mitigated the severe water shortage in receiving area, adapted to the complex changes in water demand, and aligned with the actual operational process. |
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