水利学报2025，Vol.56Issue(7)：885-897,13.DOI:10.13243/j.cnki.slxb.20240738
基于云计算的水库群实时防洪多目标风险调度模型
A multi-objective risk operation model for real-time flood control of reservoir groups based on cloud computing
摘要
Abstract
Real-time flood control operation of a multi-reservoir system is a risky operation influenced by many uncertain factors.This paper considers the uncertainty of hydrological forecast errors and establishes a multi-objective risk operation model of a multi-reservoir system with the objectives of minimizing the highest reservoir water level and minimizing the maximum discharge in the downstream section.Using the multi-objective golden eagle opti-mization algorithm(MOGEO),the"curse of dimensionality"problem is addressed from four perspectives:intelligent optimization algorithms,risk factor simulation,parallel computing,and cloud computing.And then,an improved point cloud voxel down sampling method is proposed to extract the optimal operation scheme according to the spatial distribution of the set of non-inferior solutions.The Shiguanhe river basin is selected for case study.The results show that MOGEO reduces the calculation time of the model from 1,542 s of Non-Dominated Sorting Genetic Algorithm Ⅲto 830 s.The improved Latin hypercube sampling method can ensure the sampling accuracy while reducing the calcu-lation time by 2/3.The calculation time using the cloud distributed cluster is 113 s,which is 1/6 of that on a single cloud server with 12-core parallel processing and 1/30 of the time for serial computation.关键词
水库群/实时防洪调度/不确定性/云计算/分布式集群Key words
multi-reservoir system/real-time flood control operation/uncertainty/cloud computing/distributed cluster分类
建筑与水利引用本文复制引用
陈娟,张璐,孙飞飞,邓如霞,钟平安..基于云计算的水库群实时防洪多目标风险调度模型[J].水利学报,2025,56(7):885-897,13.基金项目
国家自然科学基金项目(52479011,51909062) （52479011,51909062）
国家重点研发计划项目(2022YFC3202801) （2022YFC3202801）
