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Incorporating weather uncertainty in demand forecasts for electricity market planning

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  • C.J. Ziser
  • Z.Y. Dong
  • K.P. Wong

Abstract

A major component of electricity network planning is to ensure supply capability into the future, through generation and transmission development. Accurate forecasts of maximum demand are a crucial component of this process, with future weather conditions having a large impact on forecast accuracy. This article presents an improved methodology for the consideration of weather uncertainty in electricity demand forecasts. Case studies based on the Australian national electricity market are used to validate the proposed methodology.

Suggested Citation

  • C.J. Ziser & Z.Y. Dong & K.P. Wong, 2012. "Incorporating weather uncertainty in demand forecasts for electricity market planning," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(7), pages 1336-1346.
    • Handle: RePEc:taf:tsysxx:v:43:y:2012:i:7:p:1336-1346
    DOI: 10.1080/00207721.2011.598962
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    Cited by:

    1. Trotter, Ian Michael & Féres, José Gustavo & Bolkesjø, Torjus Folsland & de Hollanda, Lavínia Rocha, 2015. "Simulating Brazilian Electricity Demand Under Climate Change Scenarios," Working Papers in Applied Economics 208689, Universidade Federal de Vicosa, Departamento de Economia Rural.
    2. Ivan Popov & Alexander Krylatov & Victor Zakharov & Dmitry Ivanov, 2017. "Competitive energy consumption under transmission constraints in a multi-supplier power grid system," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(5), pages 994-1001, April.
    3. Hongyong Fu & Bin Dan & Xiangkai Sun, 2014. "Joint Optimal Pricing and Ordering Decisions for Seasonal Products with Weather-Sensitive Demand," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-8, March.
    4. Angel Manuel Benitez Rodriguez & Ian Michael Trotter, 2019. "Climate change scenarios for Paraguayan power demand 2017–2050," Climatic Change, Springer, vol. 156(3), pages 425-445, October.
    5. Trotter, Ian M. & Bolkesjø, Torjus Folsland & Féres, José Gustavo & Hollanda, Lavinia, 2016. "Climate change and electricity demand in Brazil: A stochastic approach," Energy, Elsevier, vol. 102(C), pages 596-604.

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