Day-ahead schedules and imbalance costs
Renewable plants commit to a production schedule for the next day, hour by hour or in 15-minute periods, and every megawatt-hour of deviation is settled at imbalance prices. For each hour, Frontwatt picks the schedule with the lowest expected cost, using the full range of the forecast and your market's price and penalty rules.
Updated
What the day-ahead schedule is
In most liberalised electricity markets, a plant or the party responsible for its balance submits a production schedule for the next day, in hourly or 15-minute periods. The name and the format differ: in Türkiye it is the KGÜP, elsewhere it is a schedule or nomination sent to the transmission system operator. After delivery, metered output is compared with the schedule, and the difference is the imbalance.
Why the median is usually not the best schedule
Imbalance prices are asymmetric. Falling short of the schedule and producing more than scheduled are priced differently, and which one costs more depends on the market and on the system’s position.
If a shortfall costs twice as much per megawatt-hour as a surplus, the expected cost is lowest where the chance of falling short is one in three, around P33 rather than P50. In general, with costs that grow in a straight line:
best quantile = cost of surplus ÷ (cost of surplus + cost of shortfall)
This is the classic newsvendor result from operations research. It is why a probabilistic forecast is worth more than a single number: you cannot pick the right quantile without the range.
Penalty bands bend the rule
Some markets add a penalty for deviations beyond a tolerance band, such as KÜPST in Türkiye. Costs are then no longer a straight line, so Frontwatt does not rely on the formula. It evaluates every candidate schedule against all forecast scenarios and keeps the one with the lowest expected total of imbalance and penalty costs.
Prices are uncertain too
Tomorrow’s imbalance prices are not known when the schedule is due. Frontwatt uses the expected price for each hour from recent market data.
An example
Four hours from the synthetic example on our homepage, as a cold front reaches a 120 MW wind farm. On that day a shortfall is the costlier mistake, so the schedule sits below the median while the front’s timing is uncertain:
| Hour | P10 | P50 | P90 | Schedule |
|---|---|---|---|---|
| 12:00 | 33 MW | 79 MW | 104 MW | 64 MW |
| 13:00 | 22 MW | 66 MW | 99 MW | 48 MW |
| 14:00 | 16 MW | 50 MW | 92 MW | 36 MW |
| 15:00 | 14 MW | 37 MW | 82 MW | 28 MW |
What you get
- For every plant and hour: the schedule, the forecast range behind it and the expected cost.
- Manual edits and an approval step before anything leaves the system.
- Exports in Excel, CSV and ENTSO-E XML.
- After delivery: the realised imbalance cost per plant and day, so you can see what the schedule actually cost.