基于改进谱聚类算法的供水管网DMA分区优化研究  

Study on DMAPartition Optimization ofWater Supply Networks Based on Improved Spectral Clustering Algorithm

在线阅读下载全文

作  者:吴永亮 范功端[2] 陈丰 曾力 蔡志鹏 Wu Yongliang;Fan Gongduan;Chen Feng;Zeng Li;Cai Zhipeng(Fujian Water Investment Digital Technology Co.,Ltd.,Fuzhou 350003,China;College of Civil Engineering,Fuzhou University,Fuzhou 350108,China)

机构地区:[1]福建省水投数字科技有限公司,福建福州350003 [2]福州大学土木工程学院,福建福州350108

出  处:《市政技术》2024年第12期55-60,181,共7页Journal of Municipal Technology

摘  要:DMA(District Metering Area)是实现供水管网低碳运行与漏损控制的重要手段,但在大多数工程案例中,往往会忽视或舍弃已有分区基础,从而造成大量资源浪费等现象。针对这一问题,提出一种基于改进谱聚类算法的DMA分区优化方案,它可以充分利用已有分区基础条件,并利用NSGA-Ⅱ算法对分区方案改造成本、管道压力和经济流速进行优化,在已有分区的基础上提出最优的二级分区解决方案。将该方法应用于L县供水管网的分区改造工程中,相比传统谱聚类算法,分区改造成本降低33.63%,最大分区压力标准差降低3.22%,非经济流速管道占比降低0.88%。结果表明,改进方法的经济性和水力性能均得到显著提升,可为同类工程提供参考。The district metering area(DMA)is the important measures to realize low-carbon operations and leakage control of the water supply networks.However,in the majority of engineering cases,the existing zoning basis is often overlooked or discarded,resulting in a considerable loss of resources.To address this issue,a DMA partition optimization scheme based on an improved spectral clustering algorithm is proposed.This scheme makes full use of the existing zoning base conditions and optimizes the zoning scheme reformation cost,the pipe pressure and economic flow rate using the NSGA-II algorithm to propose the most optimal second-level partition solution.The method was applied to a water supply pipe network zoning renovation project in County L.Compared with the traditional spectral clustering algorithm,the zoning reformation cost was reduced by 33.63%,the standard deviation of the maximum zoning pressure was reduced by 3.22%and the percentage of pipes with a non-economic flow rate was reduced by 0.88%.The results show that both economic and hydraulic performance of the methods have been significantly improved,offering a valuable reference for the similar projects.

关 键 词:供水管网 改进谱聚类算法 DMA分区 NSGA-Ⅱ算法 

分 类 号:TU991.33[建筑科学—市政工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象