A multi-agent based distributed approach for optimal control of multi-zone ventilation systems considering indoor air quality and energy use. (1st October 2020)

• Record Type: Journal Article
• Authors: Li, Wenzhuo; Wang, Shengwei
• Is Part Of: Applied energy. Volume 275(2020)
• Publication Date: 2020-10-01
• Subjects: Distributed optimal control -- Multi-agent system -- Distributed sensing and control network -- Indoor air quality -- Energy efficiency -- Multi-zone ventilation system; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2020.115371
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A multi-agent based approach is proposed for optimal control of ventilation systems. A complex optimization problem is decomposed into simple optimization problems. Optimization problems can be solved in field control devices in distributed manner. It is effective in finding the optimal solutions to compromise IAQ & energy use. It allows control systems having good reconfigurability, scalability and robustness. Abstract: A trade-off problem exists in ventilation systems to ensure acceptable indoor air quality (IAQ) with minimized energy use. It is often solved by the centralized optimization approach today. However, the dynamic operation conditions of ventilation systems and the changing expectations of users make the centralized optimal control not flexible and effective in responding to those dynamics and changes. Meanwhile, the distributed installation layouts of sensing and control networks provide appropriate application platforms for distributed optimal control. This paper therefore proposes a multi-agent based distributed approach for optimal control of multi-zone ventilation systems considering IAQ and energy use by optimizing ventilation air volumes of individual rooms and primary air-handling unit (PAU). This distributed approach decomposes the complex optimization problem into a number of simple optimization problems. Distributed agents, corresponding to individual rooms and the PAU, are assigned to handle these decomposed problems. A central coordinating agent coordinates these agents to find the optimal solutions. Two control test cases under different outdoor weather conditions are conducted on a TRNSYS-MATLAB co-simulation testbed to validate the proposed multi-agent based distributed approach for optimal control by comparing with a baseline control approach and a centralized optimal control approach. Results of the distributed approach can provide almost the same outputs as the expected optimum given by the centralized optimal control approach. The experiences of implementing the proposed distributed approach show its effectiveness in solving complex optimization problems and optimizing multi-zone ventilation systems as well as good scalability and reconfigurability.