Abstract
For the purposes of government policy concerning energy security, optimal taxation, and climate change, precise estimates of the effective factors in price elasticity of electricity demand are of principal importance. In this regard, this paper explores the effect of different factors including proportion of income spent-level, consumer academic-level, demand-types, demand time, possibility of postponing demand-level, price-level, demand-level, and awareness of participation benefits-level on price elasticity of electricity demand for Iran power system. To achieve this, a nonlinear-empirical model based on response surface methodology is proposed. Thereafter, these factors were prioritized based on their effect on price elasticity. Analysis results reveal that proportion of income spent-level has the most significant effect on the price elasticity of electricity demand while consumer academic-level has the least effect. These results could be applied by policy makers as a tool in making decisions on how to set the price of electricity.
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References
Al-Sahlawi, M. A. (1989). The demand for natural gas: a survey of price and income elasticities. The Energy Journal, 77–90.
Arisoy, I., & Ozturk, I. (2014). Estimating industrial and residential electricity demand in Turkey: a time varying parameter approach. Energy, 66, 959–964.
Assadian, M, Shirdar, M. R., Idris, M. H., Izman, S., Almasi, D., Taheri, M. M., et al. (2015). Optimisation of electrophoretic deposition parameters in coating of metallic substrate by hydroxyapatite using response surface methodology, Arabian Journal for Science and Engineering, pp. 1–11.
Brons, M., Nijkamp, P., Pels, E., & Rietveld, P. (2008). A meta-analysis of the price elasticity of gasoline demand. A SUR approach. Energy Economics, 30, 2105–2122.
Carliner, G. (1973). Income elasticity of housing demand. The Review of Economics and Statistics, 528–532.
Dergiades, T., & Tsoulfidis, L. (2008). Estimating residential demand for electricity in the United States, 1965–2006. Energy Economics, 30(5), 2722–2730.
Dornbusch, R. (1987). Open economy macroeconomics: new directions, ed: National Bureau of Economic Research Cambridge, Mass., USA.
Espey, M. (1998). Gasoline demand revisited: an international meta-analysis of elasticities. Energy Economics, 20, 273–295.
Fan, S., & Hyndman, R. J. (2011). The price elasticity of electricity demand in South Australia. Energy Policy, 39, 3709–3719.
Foley, A., Gallachóir, B. Ó., Hur, J., Baldick, R., & McKeogh, E. (2010). A strategic review of electricity systems models. Energy, 35, 4522–4530.
Gyamfi, S., Krumdieck, S., & Urmee, T. (2013). Residential peak electricity demand response—highlights of some behavioural issues. Renewable and Sustainable Energy Reviews, 25, 71–77.
Havranek, T., & Kokes, O. (2015). Income elasticity of gasoline demand: a meta-analysis. Energy Economics, 47, 77–86.
Havranek, T., Irsova, Z., & Janda, K. (2012). Demand for gasoline is more price-inelastic than commonly thought. Energy Economics, 34, 201–207.
Havranek, T., Horvath, R., Irsova, Z., & Rusnak, M. (2015). Cross-country heterogeneity in intertemporal substitution. Journal of International Economics, 96, 100–118.
He, Y., Yang, L., He, H., Luo, T., & Wang, Y. (2011). Electricity demand price elasticity in China based on computable general equilibrium model analysis. Energy, 36, 1115–1123.
Hernandez, J. A., & Koch, C. (2015). An assessment of energy consumption and price responsiveness: evidence from Dominican Republic. International Journal of Management Science and Business Administration, 1, 81–87.
Jamil, F., & Ahmad, E. (2011). Income and price elasticities of electricity demand: aggregate and sector-wise analyses. Energy Policy, 39, 5519–5527.
Kirschen, D and Strbac, G. (2005). Basic concepts from Economics, Fundamentals of Power System Economics, pp. 11–47.
Kiss, J. T., & Kocsis, I. (2014). Price and income elasticity of electricity consumption in Hungary. Environmental Engineering and Management Journal, 13, 2809–2815.
Kristianto Nugroho, Y. (2013). Developing price and production postponement strategies of substitutable product. Journal of Modelling in Management, 8, 190–211.
Li, L., & Li, M. (2014). Evaluation of energy production companies efficiency based on the combination of principal component analysis (PCA) and data envelopment analysis (DEA). Environmental Engineering and Management Journal, 13, 1147–1154.
Lijesen, M. G. (2007). The real-time price elasticity of electricity. Energy Economics, 29, 249–258.
Malik, Z., & Rashid, K. (2000). Comparison of optimization by response surface methodology with neurofuzzy methods. Magnetics IEEE Transactions on, 36, 241–257.
Maqbool S, M. Babar, and E. A. Al-Ammar, Effects of demand elasticity and price variation on load profile, in Innovative Smart Grid Technologies-Middle East (ISGT Middle East), 2011 I.E. PES Conference on, 2011, pp. 1–5.
McFadden D, C. Puig, and D. Kirschner, Determinants of the long-run demand for electricity, in Proceedings of the American Statistical Association, 1977, pp. 109–19.
Nojavan, S., Qesmati, H., Zare, K., & Seyyedi, H. (2014). Large consumer electricity acquisition considering time-of-use rates demand response programs. Arabian Journal for Science and Engineering, 39, 8913–8923.
Noordin, M. Y., Venkatesh, V. C., Sharif, S., Elting, S., & Abdullah, A. (2004). Application of response surface methodology in describing the performance of coated carbide tools when turning AISI 1045 steel. Journal of Materials Processing Technology, 145, 46–58.
Paul A. C, E. C. Myers, and K. L. Palmer, A partial adjustment model of US electricity demand by region, season, and sector, 2009.
Pielow A, R. Sioshansi, M. C. Roberts, Modeling short-run electricity demand with long-term growth rates and consumer price elasticity in commercial and industrial sectors Energy, 46, pp. 533–540, 2012.
Shirdar, M. R., Golshan, A., Izman, S., & Ghodsiyeh, D. (2014). The application of surface response methodology to the pretreatment of WC substrates prior to diamond coating. Journal of Materials Engineering and Performance, 23, 13–24.
Shirdar, M. R, Taheri, M. M., Moradifard, H., Keyvanfar, A., Shafaghat, A., Shokuhfar, T., et al. (2016). Hydroxyapatite-Titania nanotube composite as a coating layer on Co-Cr-based implants: mechanical and electrochemical optimization, Ceramics International.
Silk, J. I., & Joutz, F. L. (1997). Short and long-run elasticities in US residential electricity demand: a co-integration approach. Energy Economics, 19, 493–513.
Smolny, W. (1998). Monopolistic price setting and supply rigidities in a disequilibrium framework. Economic Theory, 11, 157–169.
Thimmapuram, P. R., & Kim, J. (2013). Consumers’ price elasticity of demand modeling with economic effects on electricity markets using an agent-based model. Smart Grid, IEEE Transactions on, 4, 390–397.
U. EIA, Annual energy outlook 2013, US Energy Information Administration, Washington, DC, 2013
Wang, K., Ouyang, Z., Krishnan, R., Shu, L., & He, L. (2015). A game theory-based energy management system using price elasticity for smart grids. Industrial Informatics, IEEE Transactions on, 11, 1607–1616.
Zhang, X.-P. (2010). Restructured electric power systems: analysis of electricity markets with equilibrium models vol. 71: John Wiley & Sons.
Acknowledgements
The authors sincerely would like to express their appreciation to the Universiti Teknologi Malaysia (UTM) for supporting this work through FRGS Grant (Vote No: 4F911) and Ministry of Higher Education (MOHE) for providing funds to carry out the research reported in this paper.
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Zin, A.A.B.M., Moradi, M. An experimental investigation of price elasticity in electricity markets using a response surface methodology. Energy Efficiency 12, 667–680 (2019). https://doi.org/10.1007/s12053-018-9672-2
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DOI: https://doi.org/10.1007/s12053-018-9672-2