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Datasets (32)
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Demand
This dataset contains national electricity demand forecast for 7 days ahead as well as all historic 7 day ahead demand forecasts. The forecast assists the industry to make efficient decisions in…
- CSV
- PNG
Demand
This dataset contains national electricity demand forecast for 2 days ahead as well as all historic 2 day ahead demand forecasts. The forecast assists the industry to make efficient decisions in…
- CSV
Demand
This dataset contains the historical and forecast profile dates used to convert our Cardinal Point forecasts into half hourly demand forecasts between the start of 2018 up to 14 Days Ahead. The…
- CSV
Demand
This dataset contains national electricity demand forecasts for 2-14 days ahead (medium term) as well as all historic 2-14 days ahead forecasts. These forecasts assist the industry to make efficient…
- CSV
- XLSX
Balancing costs
There is a file for each run type we calculate a BSUoS charge for - Interim Initial (II), Settlement Final (SF) and Reconciliation Final (RF). These are updated daily with the actual Half Hourly…,…
- CSV
- PNG
Demand
This dataset contains national electricity demand forecast for day ahead as well as all historic day ahead demand forecasts. The forecast assists the industry to make efficient decisions in balancing…
- DOC
- CSV
Demand
This section contains historic electricity demand, interconnector, hydro storage pumping, Non-BM Short Term Operating Reserve (STOR), wind and solar outturn data.
- CSV
Balancing costs
The BSUoS charge recovers the cost of day-to-day operation of the transmission system. Generators and suppliers are liable for these charges, which are calculated daily as a flat tariff for all users…
- CSV
Balancing costs
The BSUoS charge recovers the cost of day-to-day operation of the transmission system. Generators and suppliers are liable for these charges, which are calculated daily as a flat tariff for all users…
- CSV
Demand
This dataset contains incremental updates for 2-52 weeks ahead demand forecast. The forecast assist the industry to make efficient decisions in balancing their supply and demand positions.