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Aggregate electricity demand in South Africa: Conditional forecasts to 2030

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  • Inglesi, Roula

Abstract

In 2008, South Africa experienced a severe electricity crisis. Domestic and industrial electricity users had to suffer from black outs all over the country. It is argued that partially the reason was the lack of research on energy, locally. However, Eskom argues that the lack of capacity can only be solved by building new power plants. The objective of this study is to specify the variables that explain the electricity demand in South Africa and to forecast electricity demand by creating a model using the Engle-Granger methodology for co-integration and Error Correction models. By producing reliable results, this study will make a significant contribution that will improve the status quo of energy research in South Africa. The findings indicate that there is a long run relationship between electricity consumption and price as well as economic growth/income. The last few years in South Africa, price elasticity was rarely taken into account because of the low and decreasing prices in the past. The short-run dynamics of the system are affected by population growth, too After the energy crisis, Eskom, the national electricity supplier, is in search for substantial funding in order to build new power plants that will help with the envisaged lack of capacity that the company experienced. By using two scenarios for the future of growth, this study shows that the electricity demand will drop substantially due to the price policies agreed - until now - by Eskom and the National Energy Regulator South Africa (NERSA) that will affect the demand for some years.

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Bibliographic Info

Article provided by Elsevier in its journal Applied Energy.

Volume (Year): 87 (2010)
Issue (Month): 1 (January)
Pages: 197-204

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Handle: RePEc:eee:appene:v:87:y:2010:i:1:p:197-204

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Related research

Keywords: Electricity demand Forecasting South Africa;

References

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Citations

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Cited by:
  1. Inglesi-Lotz, R., 2011. "The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application," Energy Policy, Elsevier, vol. 39(6), pages 3690-3696, June.
  2. Morgan Bazilian & Patrick Nussbaumer & Hans-Holger Rogner & Abeeku Brew-Hammond & Vivien Foster & Shonali Pachauri & Eric Williams & Mark Howells & Philippe Niyongabo & Lawrence Musaba & Brian Ó Gall, 2011. "Energy Access Scenarios to 2030 for the Power Sector in Sub-Saharan Africa," Working Papers 2011.68, Fondazione Eni Enrico Mattei.
  3. Bilgili, Faik & Pamuk, Yalçın & Halıcı Tülüce, Nadide Sevil, 2010. "Short run and long run dynamics of residential electricity consumption: Homogeneous and heterogeneous panel estimations for OECD," MPRA Paper 33291, University Library of Munich, Germany, revised Jun 2011.
  4. Adom, Philip Kofi & Bekoe, William, 2013. "Modelling electricity demand in Ghana revisited: The role of policy regime changes," Energy Policy, Elsevier, vol. 61(C), pages 42-50.
  5. Lombard, Andrea & Ferreira, Sanette, 2014. "Residents' attitudes to proposed wind farms in the West Coast region of South Africa: A social perspective from the South," Energy Policy, Elsevier, vol. 66(C), pages 390-399.
  6. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio & Minea, Alina A., 2010. "Analysis and forecasting of nonresidential electricity consumption in Romania," Applied Energy, Elsevier, vol. 87(11), pages 3584-3590, November.
  7. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
  8. Zhu, Suling & Wang, Jianzhou & Zhao, Weigang & Wang, Jujie, 2011. "A seasonal hybrid procedure for electricity demand forecasting in China," Applied Energy, Elsevier, vol. 88(11), pages 3807-3815.
  9. Roula Inglesi-Lotz, 2012. "The sensitivity of the South African industrial sector’s electricity consumption to electricity price fluctuations," Working Papers 201225, University of Pretoria, Department of Economics.

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