Summary

pd4castr price forecasts aim to be 7day price forecasts are significantly more accurate than AEMO’s forecast. Primarily this is due to the fact that participants are only obligated to submit accurate available capacity in their initial bids. Price band volumes are not restructured until within, or just prior to, the predispatch time horizon.

pd4castr PD price forecasts are generally more accurate than AEMO forecasts , particularly when the forecast period is many hours into the future. AEMO price forecasts change considerably from the first predispatch to later predispatch runs as the forecast period approaches. This is primarily caused by participant's unit commitments and the repricing of volume that best matches their a participants contract/portfolio position.

pd4castr forecasts are derived in a matter of seconds by a model which is formulated by Machine Learning Algorithm (MLA) trained with historical data. This model effectively anticipates changes in participant behaviour based on known market conditions and prior to actual changes in participant behaviour in real time.

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To be disclosed with later release stages.

Input variables (features) for pd4castr predispatch

Note that more variables are used as inputs into the model than are presented in the Model Input Chart in the Home page of pd4castr. Chart variables are representative of the key variables of the model but changes in other variables will also impact the model forecast.

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