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第32届中国过程控制会议(CPCC2021)

作者： Jiahui Xu Mei Meng Jingcheng Wang Department of Automation Shanghai Jiaotong University

pump scheduling optimization is an essential guarantee for the safety and stability of water supply in water distribution networks(WDNs).However,the existing pump scheduling optimization methods are typically based on artificial experience with no systematic guidance and the empirical policy is relatively simple and not adaptive which makes it hard to implement since the real-world WDN is becoming *** this article,we attempt to address this issue by exploring data-driven approaches for pump scheduling optimization while considering arbitrary topology and no need for a hydraulic ***,the deep neural network is used to obtain the steady-state model of the ***,we use an adaptive policy to construct the loss function and use particle swarm optimization to implement online *** perform simulation studies using a realworld network in Shanghai to evaluate the effectiveness of the steady-state model and the control policy.

关键词： Water Distribution Network pump scheduling Deep Neural Network Particle Swarm Optimization

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Optimal operation of multi-storage tank multi-source system based on storage policy

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2010年第8期11卷 571-579页

作者： Hai-en FANG Jie ZHANG Jin-liang GAO School of Municipal and Environment Engineering Harbin Institute of Technology Harbin 150090 China

A two-stage method is developed to solve a new class of multi-storage tank multi-source (MTMS) systems. In the first stage, the optimal storage policy of each tank is determined according to the electricity tariff, and the ground-level storage tank is modeled as a node. In the second stage, the genetic algorithm, combined with a repairing scheme, is applied to solve the pump scheduling problem. The objective of the pump scheduling problem is to ensure that the required volume is adequately provided by the pumps while minimizing the operation cost (energy cost and treatment cost). The decision variables are the settings of the pumps and speed ratio of variable-speed pumps at time steps of the total operational time horizon. A mixed coding methodology is developed according to the characteristics of the decision variables. Daily operation cost savings of approximately 11% are obtained by application of the proposed method to a pressure zone of S. Y. water distribution system (WDS), China.

关键词： Multi-storage tank system Storage policy Genetic algorithm Repairing scheme pump scheduling

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