We seek expressions of interest from an individual or team to assist in performing a detailed review of forecasting methods for energy demand modelling. The individual or team will have knowledge and understanding of statistical methods used in the energy sector both in practical usage by the energy suppliers and those that have been used in forecasting competitions. We seek an independent researcher or consultant that can take on a lead role in this review.

The preferred candidate(s) will have a PhD in Statistics, Econometrics, or a directly related field (or a Masters degree plus significant relevant experience), with experience in using and understanding models for demand in the energy sector.

The goal of the review is to gain an understanding of the strengths and weaknesses of currently used forecasting models. Specifically, the scope of this review would be:

1. Review the methods for demand modelling that are used by energy suppliers across the globe including AEMO, Électricité de France, Southern California Edison, Energinet, and comparable organizations. In many instances, these methods are reported in publicly available reports. The review will look in detail at the forecasting models used, examination of underlying assumptions, the quantification of uncertainty, and the evaluation of the forecast uncertainty.

2. Investigate the robustness of these forecasting methods to future challenges and disruptive technologies. These challenges include the potential for strong uptake of new technologies such as EVs and battery storage, as well as changes in mobility and lifestyle patterns, and the potential for the electrification of significant parts of the industrial sector.

3. Review the winning methods from the three Global Energy Forecasting Competitions (GEFCom) where they are relevant to demand forecasting. Further review follow-up state-of-the-art statistical and machine learning research where there is empirical evidence that the proposed methods are competitive with the GEFCom results.

It is anticipated that this project will run for approximately 3-4 months.

An open Expression of Interest will close on 24 September.

Interested parties should submit an EOI to Professor Howard Bondell at howard.bondell@unimelb.edu.au and any questions can also be addressed to that contact.