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Application of artificial neural networks and fuzzy logic to long-term load forecast considering the price elasticity of electricity demand
2018; Wiley; Volume: 28; Issue: 10 Linguagem: Inglês
10.1002/etep.2606
ISSN2050-7038
AutoresSandy Tondolo de Miranda, Alzenira da Rosa Abaide, Maurício Sperandio, Moises Machado Santos, Eric Zanghi,
Tópico(s)Power Systems and Renewable Energy
ResumoInternational Transactions on Electrical Energy SystemsVolume 28, Issue 10 e2606 RESEARCH ARTICLE Application of artificial neural networks and fuzzy logic to long-term load forecast considering the price elasticity of electricity demand Sandy Tondolo de Miranda, Sandy Tondolo de Miranda Department of Electrical Engineering, Federal University of Santa Catarina, Florianópolis, SC, BrazilSearch for more papers by this authorAlzenira Abaide, Alzenira Abaide Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS, 97015-900 BrazilSearch for more papers by this authorMauricio Sperandio, Corresponding Author Mauricio Sperandio mauricio.sperandio@ufsm.br Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS, 97015-900 Brazil Correspondence Mauricio Sperandio and Moises Machado Santos, Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS 97015-900, Brazil. Email: mauricio.sperandio@ufsm.br moises.santos@unijui.edu.br Eric Zanghi, INESC Technology and Science (INESC TEC, formerly INESC Porto), Faculty of Engineering, University of Porto (FEUP), Porto, Portugal. Email: eric.zanghi@inesctec.ptSearch for more papers by this authorMoises Machado Santos, Corresponding Author Moises Machado Santos moises.santos@unijui.edu.br orcid.org/0000-0003-1681-1425 Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS, 97015-900 Brazil Correspondence Mauricio Sperandio and Moises Machado Santos, Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS 97015-900, Brazil. Email: mauricio.sperandio@ufsm.br moises.santos@unijui.edu.br Eric Zanghi, INESC Technology and Science (INESC TEC, formerly INESC Porto), Faculty of Engineering, University of Porto (FEUP), Porto, Portugal. Email: eric.zanghi@inesctec.ptSearch for more papers by this authorEric Zanghi, Corresponding Author Eric Zanghi eric.zanghi@inesctec.pt INESC Technology and Science (INESC TEC, formerly INESC Porto), Faculty of Engineering, University of Porto (FEUP), Porto, Portugal Correspondence Mauricio Sperandio and Moises Machado Santos, Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS 97015-900, Brazil. Email: mauricio.sperandio@ufsm.br moises.santos@unijui.edu.br Eric Zanghi, INESC Technology and Science (INESC TEC, formerly INESC Porto), Faculty of Engineering, University of Porto (FEUP), Porto, Portugal. Email: eric.zanghi@inesctec.ptSearch for more papers by this author Sandy Tondolo de Miranda, Sandy Tondolo de Miranda Department of Electrical Engineering, Federal University of Santa Catarina, Florianópolis, SC, BrazilSearch for more papers by this authorAlzenira Abaide, Alzenira Abaide Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS, 97015-900 BrazilSearch for more papers by this authorMauricio Sperandio, Corresponding Author Mauricio Sperandio mauricio.sperandio@ufsm.br Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS, 97015-900 Brazil Correspondence Mauricio Sperandio and Moises Machado Santos, Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS 97015-900, Brazil. Email: mauricio.sperandio@ufsm.br moises.santos@unijui.edu.br Eric Zanghi, INESC Technology and Science (INESC TEC, formerly INESC Porto), Faculty of Engineering, University of Porto (FEUP), Porto, Portugal. Email: eric.zanghi@inesctec.ptSearch for more papers by this authorMoises Machado Santos, Corresponding Author Moises Machado Santos moises.santos@unijui.edu.br orcid.org/0000-0003-1681-1425 Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS, 97015-900 Brazil Correspondence Mauricio Sperandio and Moises Machado Santos, Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS 97015-900, Brazil. Email: mauricio.sperandio@ufsm.br moises.santos@unijui.edu.br Eric Zanghi, INESC Technology and Science (INESC TEC, formerly INESC Porto), Faculty of Engineering, University of Porto (FEUP), Porto, Portugal. Email: eric.zanghi@inesctec.ptSearch for more papers by this authorEric Zanghi, Corresponding Author Eric Zanghi eric.zanghi@inesctec.pt INESC Technology and Science (INESC TEC, formerly INESC Porto), Faculty of Engineering, University of Porto (FEUP), Porto, Portugal Correspondence Mauricio Sperandio and Moises Machado Santos, Department of Electromechanical and Power Systems, Federal University of Santa Maria, Campus Camobi, Santa Maria, RS 97015-900, Brazil. Email: mauricio.sperandio@ufsm.br moises.santos@unijui.edu.br Eric Zanghi, INESC Technology and Science (INESC TEC, formerly INESC Porto), Faculty of Engineering, University of Porto (FEUP), Porto, Portugal. Email: eric.zanghi@inesctec.ptSearch for more papers by this author First published: 04 May 2018 https://doi.org/10.1002/etep.2606Citations: 7Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Summary Over the past few decades, the behavior of electricity consumption has been changing, especially because of improvements in the distributed generation segment and technological innovations presented by smart grids. The use of microgeneration and the availability of electricity pricing in real time allow consumers to control their consumption, or generation, according to market conditions. This new dynamic tends to increasingly change the price elasticity of electricity demand, by indicating the need to readjust load forecasting models. In this market environment, in addition to providing robust estimates for the planning and operation of electric power systems, load forecasting models have become fundamental in the context of demand management. Thus, this paper proposes to develop an artificial neural network and fuzzy logic for load forecasting to perform an efficiency analysis. This system is able to provide estimates of the elasticity of electricity demand behavior with more satisfactory results. To do so, improvements in the neural network with multilayer perceptron are proposed. In this case, the adaptation of parameters to correlate variations in consumption with the changes in electricity tariffs was developed. The addition of this new structure produced better results compared with the conventional neural network. Computer tests were conducted using historical data from the ISO New England Inc and PJM Interconnection. Price elasticity estimates of electricity demand showed a sharp increase of demand in relation to the elasticity behavior. Citing Literature Volume28, Issue10October 2018e2606 RelatedInformation
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