Long-term Price Forecasting

Beyond about 2 years, generator bidding behaviour and weather conditions are almost impossible to predict based on historical trends and so these inputs are discarded. Half hourly load traces are developed using historical reference load patterns which are manipulated to meet NEMMCO and TNSP forecasts of annual energy and peak summer and winter demand forecasts such as the Low / Medium / High energy growth with 10% / 50% / 90% probability of exceedence demand forecasts.


Bidding and outage behaviour are drawn from long term averages and predicted generator behaviour as the market evolves.


Using 2-4-C®, we are able to extend price forecasts as far out in time as could be practically needed.

For more information on 2-4-C®, download our 2-4-C® brochure.

Medium-term Price Forecasting

Weather and bidding patterns are harder to predict 3-to-24 months ahead. In the medium-term framework, loads are forecast using advanced time-series analysis and multi-variate random processes for load co-incidence between the states. Weather correction via piece-wise regression and neural net outcomes is possible due to ROAM's ongoing subscription to the Bureau's 3-month outlook, which details the likelihood of hot or cool conditions across Australia in the months to come.


Bidding and outage behaviours are drawn from long term averages and trends as applied in our ROAM Insight publication, and development is continuing on this component of the model input.


Benchmarking and Backcasting

The 2-4-C® half-hourly dispatch engine is utilised to solve the system for the forecast period. The figure below provides a sample of a 'back-casting' simulation study which we complete regularly to callibrade our data sets. This demonstrates the accuracy of our forecasting methodologies and has been used for 'what if' assessment and to study market anomalies.


Figure A: Sample of a 2-4-C® backcast compared with actual pool prices

Please contact us for more information on any of the above services