Modeling Multi-horizon Electricity Demand Forecasts in Australia: A Term Structure Approach

, Martin, Vance, & Tian, Jing (2023) Modeling Multi-horizon Electricity Demand Forecasts in Australia: A Term Structure Approach. Energy Journal, 44(3), pp. 251-266.

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Description

The Australian Electricity Market Operator generates one-day ahead electricity demand forecasts for the National Electricity Market in Australia and updates these forecasts over time until the time of dispatch. Despite the fact that these forecasts play a crucial role in the decision-making process of market participants, lit-tle attention has been paid to their evaluation and interpretation. Using half-hourly data from 2011 to 2015 for New South Wales and Queensland, it is shown that the official half-hourly demand forecasts do not satisfy the econometric properties required of rational forecasts. Instead there is a relationship between forecasts and forecast horizon similar to a term structure model of interest rates. To study the term structure of demand forecasts, a factor analysis that uses a small set of latent factors to explain the common variation among multiple observables is imple-mented. A three-factor model is identified with the factors admitting interpretation as the level, slope and curvature of the term structure of forecasts. The validity of the model is reinforced by assessing the economic value of demand forecasts. It is demonstrated that simple adjustments to long-horizon electricity demand forecasts based on the three estimated factors can enhance the informational content of the official forecasts.

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ID Code: 249299
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
ORCID iD:
Hurn, Stanorcid.org/0000-0002-6134-7943
Measurements or Duration: 16 pages
Keywords: Economic value, Electricity demand, Multi-horizon forecasts, Term structure
DOI: 10.5547/01956574.44.2.SHUR
ISSN: 0195-6574
Pure ID: 171908223
Divisions: Current > QUT Faculties and Divisions > Faculty of Business & Law
Current > Schools > School of Economics & Finance
Copyright Owner: 2023 IAEE
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Deposited On: 28 Jun 2024 00:36
Last Modified: 28 Jun 2024 02:21