摘要
在面临诸多不确定性情景时,传统的供水管网最优运行方案,存在供水安全风险。在优化运行研究中耦合需水不确定性情景,即在随机型优化运行模型中,提出机会约束形式的鲁棒性要求,可强化最优方案的安全供水能力。同时,针对rccGA算法缺陷,引入区间均匀采样方法、改进的个体适应度排序准则、保留较优个体策略、直接遗传概率、存活代数计算规则等改进策略,形成mccGA算法,并通过Anytown案例性能测试,证明了该算法能加快收敛速度,其稳定性和求解精度都明显增强;C-Town工程实例,同样验证了该方法框架对实际应用中考虑不确定性复杂优化运行问题具备良好适用性。
Under many uncertain scenarios, the traditional optimal operational solution for water distribution system(WDS) has insufficient applicability. This paper proposes the framework of WDS optimization operation coupling demand uncertainty, the stochastic optimization operation model for WDS where robustness requirement is in the form of chance constraint, aiming at strengthening the safety of water supply. Meanwhile, in order to handle the bad performance of rccGA, series of targeted improvement strategies, such as interval uniform sampling rule, the revised rank rule, strategy of storing better individuals, direct genetic probability, the calculus of age, are introduced to form mccGA. The performance test of Anytown case proves that mccGA can speed up the convergence, and its stability and solution accuracy are significantly enhanced. The C-Town project example also shows that the method framework has good applicability, when used to solve the complex optimization problems considering uncertainties in practical applications.
作者
张朝
刘海星
顾建强
商华
赵梦珂
张弛
周惠成
黄河洵
Zhang Chao;Liu Haixing;Gu Jianqiang;Shang Hua;Zhao Mengke;Zhang Chi;Zhou Huicheng;Huang Hexun(School of Hydraulic Engineering,Dalian University of Technology,Dalian 116024,China;Department of Management and Economics,Dalian University of Technology 9 Daliaji 116024,China;Shenzhen Water Affairs(Group)Co.,Ltd.,Shenzhen 518031,China;Engineering Laboratory for Wastewater treatment and reuse in Shenzhen,Shenzhen 518031,China)
出处
《给水排水》
CSCD
北大核心
2019年第11期124-130,共7页
Water & Wastewater Engineering
基金
国家自然科学基金青年项目(51708086)
国家自然科学基金国际合作交流项目(51811530314)
国家重点研发计划项目(2016YFC0402203)
中央高校基本科研业务费资助(DUT18RC(3)072)
关键词
需水不确定性
供水管网系统
优化运行
mccGA
LHS
Demand uncertainty
Water distribution system
Optimal operation
mccGA
Latin hypercube sampling