Evaluating factors responsible for energy consumption: Connection weight approach

Oludolapo Akanni Olanrewaju, Charles Mbohwa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Various governments and stakeholders are established across the globe to respond to various energy challenges that has led to one or more energy policy development. A proper analysis of what contributes to energy consumption will assist in the development of policies needed for the conservation of energy consumption. This study made use of the connection weight approach as an instrument of the Artificial Neural Network (ANN) to evaluate the contributions of activity, structure and intensity factors to energy consumption in the Canadian industrial sector. From the evaluation, intensity contributed 46.5 %, whereas activity and structure contributed 32.6 % and 20.9 %. This is an indication that policies and strategies should be developed more on intensity to achieve energy saving.

Original languageEnglish
Title of host publication2016 IEEE Electrical Power and Energy Conference, EPEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509019199
DOIs
Publication statusPublished - 5 Dec 2016
Event2016 IEEE Electrical Power and Energy Conference, EPEC 2016 - Ottawa, Canada
Duration: 12 Oct 201614 Oct 2016

Publication series

Name2016 IEEE Electrical Power and Energy Conference, EPEC 2016

Conference

Conference2016 IEEE Electrical Power and Energy Conference, EPEC 2016
Country/TerritoryCanada
CityOttawa
Period12/10/1614/10/16

Keywords

  • Artificial Neural Network
  • connection weight
  • energy consumption
  • policies

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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