Model updated
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8th August 2023
Summary
The retraining process resulted in two new models, one for PD and one for 7day price forecast. After considerable experimentation we retrained the price forecasting models with a considerable increase in accuracy (see validation results table below comparing the previous models with the new models).
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Predispatch model | p7day model | |
|---|---|---|
Model_id | 20230729_213406_CB_2 | 20230213_012319_CB_7D_1 |
Previous model release date | 20th April 2023 | 20th April 2023 |
Latest release date (after retraining) | 1st 8th August 20231st | 8th August 2023 |
Machine Learning Algorithm | Ensemble predictor: gradient boosting | Ensemble predictor: gradient boosting |
Training Period | 1st October 2020 to 20th July 2023 | 1st October 2020 to 20th July 2023 |
Hyper-parameter type | A | A |
Hyper-parameter notes | No weighting across time periods | No weighting across time periods |
Target | Dispatchprice (30min resolution) | Dispatchprice (30min resolution) |
Input (and training) variables | PREDISPATCHPRICE rrp DISPATCHPRICE last 3 day average actual RRP for same time PREDISPATCHREGIONSUM (intervention = 0) hours_out time_of_day day_type (weekday_or_weekend) dispatchableload netinterchage (availablegeneration - uigf) (dispatchablegeneration - scheduled_clearedmw) ss_solar_clearedmw ss_solar_uigf ss_wind_clearedmw ss_wind_uigf totaldemand totalintermittentgeneration | STPASA_REGIONSOLUTION hours_out time_of_day day_type (weekday_or_weekend) aggregatepasaavailability aggregatescheduledload netinterchangeunderscarcity aggregatecapacityavailable ss_solar_cleared ss_wind_uigf ss_wind_cleared ss_solar_uigf demand10 demand50 totalintermittentgeneration demand_and_nonschedgen |
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