Multi-agent Gaussian Adaptive Resonance Theory Map for building energy control and thermal comfort management of UCLan's WestLakes Samuel Lindow Building

  • Maizura Mokhtar
  • , Xiongwei Liu
  • , Joe Howe

Research output: Contribution to journalJournal Articlepeer-review

Abstract

This paper presents a Gaussian Adaptive Resonance Theory Map (gARTMAP) incorporated to a multi-agent system (MAS) for building intelligent heat management system (IHMS), or the gARTMAP-MAS IHMS. The gARTMAP aims to maintain the desired space temperature defined by the building occupants (thermal comfort management) and improve energy efficiency by intelligently controlling the energy flow and usage in the building (building energy control) with minimal waste. The gARTMAP-MAS IHMS is a three-layer MAS, consisting of an agent in the Source Layer responsible for building energy control, agents in the User Layer for thermal comfort management, and an agent in the Mediator Layer which mediates the communication between the other two layers. Existing MAS typically uses a rule-based approach for its agents, and the rules are generally pre-defined. The incorporation of the gARTMAP to the agents provides additional adaptive capabilities via the use of its online learning mechanism. Simulation results demonstrated that the gARTMAP-MAS IHMS provides better (automated) energy control and thermal comfort management for a building environment in comparison to the existing rule-based MAS approach.
Original languageEnglish
Pages (from-to)504-516
JournalEnergy and Buildings
Volume80
Early online date6 Jun 2014
DOIs
Publication statusPublished online - 6 Jun 2014

Keywords

  • multi-agent system
  • artificial neural network
  • gaussian classification
  • building heat management
  • artificial intelligence
  • intelligent building energy management system

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