:: Volume 22, Issue 4 (2-2020) ::
IJE 2020, 22(4): 125-152 Back to browse issues page
A Fuzzy Multi-agent System with Virtual Sensors for Energy Management in the Cooling System
Laya Kashfi * , Mohammad Reza Akbarzadeh Tutunchi , Mohammad Hossein Yaghmaee-M
Department of Electrical and Computer Engineering, Islamic Azad University, Mashhad, Iran , lkashfi@gmail.com
Abstract:   (1891 Views)
The design of Building Intelligence Energy Management Systems (BIEMS) in the air conditioning sector is a complicated multi-objective problem for large buildings with big engine rooms and scattered inputs that it must provide simultaneously maintaining system stability, adapting to time-varying conditions, reducing energy dissipation and maintaining proper air quality. To achieve these at times conflicting objectives, using a distributed control approach is appropriate for building energy management of these buildings. In this paper, a Cooperative Multi Agent-Building Management System (CMA-BMS) equipped with fuzzy controllers and virtual sensors is proposed, in which each of the agents controls one of the main components of the cooling engine room in the HVAC's primary circuit and contrary to many previous works, the topology of them is horizontal, and each agent operates independently and in parallel, which leads to faster performance, easier error detection, and more extensibility. For modeling, the virtual sensors implemented with Radial Base Function (RBF) neural networks are utilized, which also have the role of actual sensor backup. To evaluate the project, two BEMSs are designed and tested with a conventional centralized and the proposed strategies, where simulation results indicate that the proposed design is less processor and memory intensive, and the fuzzy controllers show a better performance in terms of energy consumption versus the non-fuzzy controllers
Keywords: Building energy management system, Cooperative multi agent system, Fuzzy control, Smart grid, Soft sensor, RBF neural network
Full-Text [PDF 921 kb]   (670 Downloads)    
Type of Study: Research | Subject: Smart Grids
Received: 2019/06/12 | Accepted: 2020/08/11 | Published: 2020/02/29


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Volume 22, Issue 4 (2-2020) Back to browse issues page