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2018 | OriginalPaper | Chapter

Prediction of Electricity Consumption for Residential Houses in New Zealand

Authors : Aziz Ahmad, Timothy N. Anderson, Saeed Ur Rehman

Published in: Smart Grid and Innovative Frontiers in Telecommunications

Publisher: Springer International Publishing

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Abstract

Residential consumer’s demand of electricity is continuously growing, which leads to high greenhouse gas emissions. Detailed analysis of electricity consumption characteristics for residential buildings is needed to improve efficiency, availability and to plan in advance for periods of high electricity demand. In this research work, we have proposed an artificial neural network based model, which predicts the energy consumption of a residential house in Auckland 24 h in advance with more accuracy than the benchmark persistence approach. The effects of five weather variables on energy consumption was analyzed. Further, the model was experimented with three different training algorithms, the levenberg-marquadt (LM), bayesian regularization and scaled conjugate gradient and their effect on prediction accuracy was analyzed.

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Literature
1.
go back to reference Lukas, G.S., Ugursal, V.I.: Modeling of end-use energy consumption in the residential sector: a review of modelling techniques. Renew. Sustain. Energy Rev. 13, 1819–1835 (2009)CrossRef Lukas, G.S., Ugursal, V.I.: Modeling of end-use energy consumption in the residential sector: a review of modelling techniques. Renew. Sustain. Energy Rev. 13, 1819–1835 (2009)CrossRef
2.
3.
go back to reference Xia, C., Wang, J., McMenemy, K.: Short, medium and long term load forecasting model and virtual load forecaster based on radial basis function neural networks. Int. J. Electr. Power Energy Syst. 32, 743–750 (2010)CrossRef Xia, C., Wang, J., McMenemy, K.: Short, medium and long term load forecasting model and virtual load forecaster based on radial basis function neural networks. Int. J. Electr. Power Energy Syst. 32, 743–750 (2010)CrossRef
4.
go back to reference Maia, C., Goncalves, M.: A methodology for short-term electric load forecasting based on specialized recursive digital filters. Comput. Ind. Eng. 57, 724–731 (2009)CrossRef Maia, C., Goncalves, M.: A methodology for short-term electric load forecasting based on specialized recursive digital filters. Comput. Ind. Eng. 57, 724–731 (2009)CrossRef
6.
go back to reference Tso, G.K.F., Yau, K.K.W.: A study of domestic energy usage pattern in Hong Kong. Energy 28, 1671–1682 (2003)CrossRef Tso, G.K.F., Yau, K.K.W.: A study of domestic energy usage pattern in Hong Kong. Energy 28, 1671–1682 (2003)CrossRef
7.
go back to reference Al-Garni, A.Z., Zubair, S.M., Nizami, J.S.: A regression model for electric energy consumption forecasting in Eastern Saudi Arabia. Energy 19, 1043–1049 (1994)CrossRef Al-Garni, A.Z., Zubair, S.M., Nizami, J.S.: A regression model for electric energy consumption forecasting in Eastern Saudi Arabia. Energy 19, 1043–1049 (1994)CrossRef
8.
go back to reference Yan, Y.Y.: Climate and residential electricity consumption in Hong Kong. Energy 23, 17–20 (1998)CrossRef Yan, Y.Y.: Climate and residential electricity consumption in Hong Kong. Energy 23, 17–20 (1998)CrossRef
9.
go back to reference Ranjan, M., Jain, V.K.: Modelling of electrical energy consumption in Delhi. Energy 24, 351–361 (1999)CrossRef Ranjan, M., Jain, V.K.: Modelling of electrical energy consumption in Delhi. Energy 24, 351–361 (1999)CrossRef
10.
go back to reference Egelioglu, F., Mohamada, A.A., Guven, H.: Economic variables and electricity consumption in Northern Cyprus. Energy 26, 355–362 (2001)CrossRef Egelioglu, F., Mohamada, A.A., Guven, H.: Economic variables and electricity consumption in Northern Cyprus. Energy 26, 355–362 (2001)CrossRef
11.
go back to reference Ho, L.K., Hsu, Y.Y., Chen, F.C., Lee, E.T., Liang, C.C., Lai, S.T., Chen, K.K.: Short term load forecasting of Taiwan power system using a knowledge-based expert system. IEEE Trans. Power Syst. 5, 1214–1221 (1990)CrossRef Ho, L.K., Hsu, Y.Y., Chen, F.C., Lee, E.T., Liang, C.C., Lai, S.T., Chen, K.K.: Short term load forecasting of Taiwan power system using a knowledge-based expert system. IEEE Trans. Power Syst. 5, 1214–1221 (1990)CrossRef
12.
go back to reference Rahman, S., Hazim, O.: A generalized knowledge-based short-term load-forecasting technique. IEEE Trans. Power Syst. 8, 508–514 (1993)CrossRef Rahman, S., Hazim, O.: A generalized knowledge-based short-term load-forecasting technique. IEEE Trans. Power Syst. 8, 508–514 (1993)CrossRef
13.
go back to reference Moghram, I., Rahman, S.: Analysis and evaluation of five short-term load forecasting techniques. IEEE Trans. Power Syst. 4, 1484–1491 (1989)CrossRef Moghram, I., Rahman, S.: Analysis and evaluation of five short-term load forecasting techniques. IEEE Trans. Power Syst. 4, 1484–1491 (1989)CrossRef
14.
go back to reference Khotanzad, A., Afhkhami-Rohani, R., Maratukulam, D.: ANNSTLF artificial neural network short-term load forecaster generation three. IEEE Trans. Neural Netw. 13, 1413–1422 (1998) Khotanzad, A., Afhkhami-Rohani, R., Maratukulam, D.: ANNSTLF artificial neural network short-term load forecaster generation three. IEEE Trans. Neural Netw. 13, 1413–1422 (1998)
15.
go back to reference Eugen, D.: The use of NARX neural networks to predict chaotic time series. WSEAS Trans. Comput. Res. 3, 182–191 (2008) Eugen, D.: The use of NARX neural networks to predict chaotic time series. WSEAS Trans. Comput. Res. 3, 182–191 (2008)
16.
go back to reference Yadav, A.K., Chandel, S.S.: Solar radiation prediction using artificial neural network techniques: a review. Renew. Sustain. Energy Rev. 33, 772–781 (2014)CrossRef Yadav, A.K., Chandel, S.S.: Solar radiation prediction using artificial neural network techniques: a review. Renew. Sustain. Energy Rev. 33, 772–781 (2014)CrossRef
Metadata
Title
Prediction of Electricity Consumption for Residential Houses in New Zealand
Authors
Aziz Ahmad
Timothy N. Anderson
Saeed Ur Rehman
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-94965-9_17

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