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An intelligent agent based approach for energy management in commercial buildings

Hagras, H and Packham, I and Vanderstockt, Y and McNulty, N and Vadher, A and Doctor, F (2008) An intelligent agent based approach for energy management in commercial buildings. In: UNSPECIFIED, ? - ?.

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Abstract

Global warming is becoming one of the serious issues facing humanity. Several initiatives have been introduced to deal with global warming including the Kyoto Protocol which assigned mandatory targets for the reduction of greenhouse gas emissions to signatory nations. However, over the last decade, commercial buildings worldwide have experienced massive growth in energy costs. This was caused by the expansion in the use of air conditioning and artificial lighting as well as an ever increasing energy demand for computing services. Existing Building Management Systems (BMSs) have, generally, failed to fully optimize energy consumption in commercial buildings. This is because they lack control systems that can react intelligently and automatically to anticipated changes in ambient weather conditions and the many other environmental variables typically associated with large buildings. In this paper, we present a novel agent based system entitled Intelligent Control of Energy (ICE) for energy management in commercial buildings. ICE uses different Computational Intelligence (CI) techniques (including fuzzy systems, neural networks and genetic algorithms) to 'learn' a buildings thermal response to many variables including the outside weather conditions, internal occupancy requirements and building plant responses. ICE then uses CI based algorithms which work in real-time with the building's existing BMS to minimize the building's energy demand. We will show how the use of ICE will allow significant energy cost savings, while still maintaining customer-defined comfort levels. © 2008 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: IEEE International Conference on Fuzzy Systems
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 21 Jan 2013 16:35
Last Modified: 28 Nov 2017 16:15
URI: http://repository.essex.ac.uk/id/eprint/4844

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