A P2P Algorithm for Energy Saving of a Parallel-Connected Pumps System

  • Qianchuan ZhaoEmail author
  • Xuetao Wang
  • Yifan Wang
  • Ziyan Jiang
  • Yunchuang Dai
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 890)


A distributed optimal control algorithm is investigated, in this paper, to deal with the problem in a peer-to-peer (P2P) control setting for parallel pumps in heating, ventilation, and air-conditioning (HVAC) systems. Each pump is equipped with a controller and becomes an intelligent node (as a peer), and nodes are equal, self-organizing, and mutually coordinated. When the HVAC system provides the pressure difference and flow rate, each intelligent node applies the random generation of the speed ratio samples method. Then, the nodes coordinate with each other and constantly optimize the speed ratio of each pump, so that the total energy consumption of the system tends to be minimum. Simulation experiment results are provided to demonstrate the performance of the proposed algorithm.


Distributed Peer-to-peer (P2P) Pump in parallel Speed ratio Optimal control 



This work was supported by the National Key Research and Development Project of China (No. 2017YFC0704100 entitled New Generation Intelligent Building Platform Techniques, and 2016YFB0901900) and the National Natural Science Foundation of China (No. 61425027), the 111 International Collaboration Program of China under Grant B06002, BP2018006 and Special fund of Suzhou-Tsinghua Innovation Leading Action (Project Number: 2016SZ0202).

We appreciate the constructive and helpful comments from anonymous reviews and conference organizers.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Qianchuan Zhao
    • 1
    Email author
  • Xuetao Wang
    • 1
  • Yifan Wang
    • 1
  • Ziyan Jiang
    • 2
  • Yunchuang Dai
    • 2
  1. 1.Tsinghua National Laboratory for Information Science and Technology, Department of AutomationCenter for Intelligent and Networked Systems, Tsinghua UniversityBeijingChina
  2. 2.Building Energy Research Center, Tsinghua UniversityBeijingChina

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