Forecasting Australian Electricity Generation by Fuel Mix

Hanlin Shang, Lin Han, Stefan Trueck

Research output: Working paper/PreprintPreprint

1 Downloads (Pure)

Abstract

Electricity demand and generation have become increasingly unpredictable with the growing share of variable renewable energy sources in the power system. Forecasting electricity supply by fuel mix is crucial for market operation, ensuring grid stability, optimizing costs, integrating renewable energy sources, and supporting sustainable energy planning. We introduce two statistical methods, centering on forecast reconciliation and compositional data analysis, to forecast short-term electricity supply by different types of fuel mix. Using data for five electricity markets in Australia, we study the forecast accuracy of these techniques. The bottom-up hierarchical forecasting method consistently outperforms the other approaches. Moreover, fuel mix forecasting is most accurate in power systems with a higher share of stable fossil fuel generation.
Original languageEnglish
PublisherArxiv
Number of pages25
DOIs
Publication statusSubmitted - 29 Oct 2025
Externally publishedYes

Keywords

  • Electricity Markets
  • Fuel Mix Forecasting
  • Compositional Data Analysis
  • Renewable Energy Integration
  • Forecast Reconciliation

Fingerprint

Dive into the research topics of 'Forecasting Australian Electricity Generation by Fuel Mix'. Together they form a unique fingerprint.

Cite this