 Modelling changes to electricity demand load duration curves as a consequence of predicted climate change for AustraliaMarcus J. Thatcher Energy, 2007, vol. 32, issue 9, 1647-1659 Abstract: In this paper, we describe a method for constructing regional electricity demand data sets at 30min intervals, which are consistent with climate change scenarios. Specifically, we modify a commonly used linear regression model between regional electricity demand and climate to also describe intraday variability in demand so that regional load duration curves (LDCs) can be predicted. The model is evaluated for four different Australian states that are participants in the Australian National Electricity Market (NEM) and the resultant data sets are found to reproduce each state's LDCs with reasonable accuracy. We also apply the demand model to CSIRO's Mk 3 global climate model data sets that have been downscaled to 60km resolution using CSIRO's conformal-cubic atmospheric model to estimate how LDCs change as a consequence of a 1°C increase in the average temperature of Australian state capital cities. These regional electricity demand data sets are then useful for economic modelling of electricity markets such as the NEM. Keywords: Load modelling; Degree days; Anthropogenic heating; Atmospheric modelling (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:32:y:2007:i:9:p:1647-1659 DOI: 10.1016/j.energy.2006.12.005 Access Statistics for this article Energy is currently edited by Henrik Lund and Mark J. Kaiser More articles in Energy from Elsevier |
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