Decentralized Optimization Algorithms for Variable Speed Pumps Operation Based on Local Interaction Game

A fully distributed optimal control strategy for the parallel variable speed pumps in heating, ventilation, and air-conditioning (HVAC) systems is proposed. Compared with the traditional centralized method, the efficient control and coordination are scattered to every updated smart pump without the need for a monitoring host. Similar to the structure, mechanism, and characteristics of biological communities, a smart pump can communicate with adjacent nodes and operate collaboratively to complete pumps group operation with the least total power consumption under load demand and system constraints. And a decentralized optimization method that is decentralized estimation of distribution algorithm (DEDA) under local interaction games framework has been transplanted to the proposed structure to optimize the pumps working in parallel mode. Besides, convergence property of the two novel mechanisms is analyzed theoretically. Finally, simulation studies have been conducted based on the models of a physical pumps system, and the performance of the proposed algorithm is compared with centralized algorithms in terms of both effectiveness and stability. The results provide support for the validity of the proposed algorithms and control structure.

[1]  Qingfu Zhang,et al.  On the convergence of a class of estimation of distribution algorithms , 2004, IEEE Transactions on Evolutionary Computation.

[2]  HaiBin Duan,et al.  An evolutionary potential game theoretic approach for the K -COVER problem in multi-UAV sensor networks , 2016 .

[3]  H. Young.  Individual Strategy and Social Structure , 2020 .

[4]  Yuguang Fang,et al.  Joint Channel and Power Allocation in Wireless Mesh Networks: A Game Theoretical Perspective , 2008, IEEE Journal on Selected Areas in Communications.

[5]  Shantanu Chakraborty,et al.  Multi-Agent based Distributed Optimization Architecture for Energy-Management Systems with Physically Coupled Dynamic Subsystems , 2015 .

[6]  Radhika Nagpal,et al.  Designing Collective Behavior in a Termite-Inspired Robot Construction Team , 2014, Science.

[7]  Yi Jiang,et al.  A decentralized algorithm for optimal distribution in HVAC systems , 2016 .

[8]  Paul Waide,et al.  Energy-Efficiency Policy Opportunities for Electric Motor-Driven Systems , 2011 .

[9]  Jason R. Marden,et al.  Cooperative Control and Potential Games , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[10]  Maksim V. Dolgopolik.  Smooth exact penalty functions: a general approach , 2016, Optim. Lett..

[11]  L. Shapley,et al.  REGULAR ARTICLEPotential Games , 1996 .

[12]  Jason R. Marden,et al.  Joint Strategy Fictitious Play with Inertia for Potential Games , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[13]  Qun Chen,et al.  A direct optimal control strategy of variable speed pumps in heat exchanger networks and experimental validations , 2015 .

[14]  A. Stierle,et al.  Designing Collective Behavior in a Termite-Inspired Robot Construction Team , 2014, Science.

[15]  Hao Yu,et al.  Development of a distributed artificial fish swarm algorithm to optimize pumps working in parallel mode , 2018 .

[16]  Zhao Tianyi,et al.  On-line optimization control method based on extreme value analysis for parallel variable-frequency hydraulic pumps in central air-conditioning systems , 2012 .

[17]  Augusto Nelson Carvalho Viana,et al.  Optimization of parallel variable-speed-driven centrifugal pumps operation , 2008 .

[18]  Alagan Anpalagan,et al.  Opportunistic Spectrum Access in Cognitive Radio Networks: Global Optimization Using Local Interaction Games , 2012, IEEE Journal of Selected Topics in Signal Processing.

[19]  Jr-Shian Chen,et al.  An enhanced genetic algorithm for bi-objective pump scheduling in water supply , 2009, Expert Syst. Appl..

[20]  S. Umashankar,et al.  A comprehensive review on energy efficiency enhancement initiatives in centrifugal pumping system , 2016 .

[21]  Jason R. Marden,et al.  Regret based dynamics: convergence in weakly acyclic games , 2007, AAMAS '07.

[22]  Pawel Olszewski,et al.  Genetic optimization and experimental verification of complex parallel pumping station with centrifugal pumps , 2016 .

[23]  Rong Su,et al.  Learning-Based Hierarchical Distributed HVAC Scheduling With Operational Constraints , 2018, IEEE Transactions on Control Systems Technology.

[24]  Stephen Treado,et al.  A review of multi-agent systems concepts and research related to building HVAC control , 2016 .

[25]  L. Shapley,et al.  Potential Games , 1994 .

[26]  İsmail Yabanova,et al.  Thermal monitoring and optimization of geothermal district heating systems using artificial neural network: A case study , 2012 .

[27]  Gonggui Chen,et al.  Chaotic improved PSO-based multi-objective optimization for minimization of power losses and L index in power systems , 2014 .