Applying artificial neural networks to promote behaviour change for saving residential energy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Authors

Colleges, School and Institutes

External organisations

  • Plymouth University

Abstract

In this paper Artificial Neural Networks (ANNs) is used to model effects of various human behaviour on energy consumption of the residential buildings in the UK. A virtual model of a bungalow has been developed in which various aspects of the, physical changes in the building such as wall and floor insulation, single and double glazing combined by the human behaviour aspects such as thermostat setting, various periods of door and/or window opening etc. are modelled using EnergyPlus software for evaluating energy consumption for a combination of scenarios. ANNs were then used to learn the effects of various human behaviours on energy consumption. The results demonstrated that the ANN is capable of learning the effects that changes in the human behaviour have in evaluating energy saving in residential buildings and it generated results very quickly for unseen cases.

Details

Original languageEnglish
Title of host publicationProceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjunction with ICINCO 2014
Publication statusPublished - 1 Jan 2014
EventInternational Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjuction with the International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014 - Vienna, Austria
Duration: 1 Sep 20143 Sep 2014

Conference

ConferenceInternational Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjuction with the International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014
CountryAustria
CityVienna
Period1/09/143/09/14