Output against schedule
Forecast by site and by hour, with the gap in MWh, revised whenever a new weather forecast comes in.
The forecast for each site is revised through the day, in time for you to correct your intraday position before the imbalance goes to settlement.
Minute‑by‑minute output sits in SCADA and the weather forecast comes from an outside provider, while bids go out from a market platform run by another team. By the time someone puts the three together, the last intraday session has closed and the imbalance is on its way to settlement.
The schedule is fixed the day before, with whatever forecast was available when the day‑ahead market closed. If nobody revises it during the morning, the gap only shows up in the system operator's settlement.
Temperatures and vibrations stay in SCADA and the maintenance history in the O&M system. A failing gearbox gives warning weeks ahead, and comparing turbines one by one does not fit into anyone's day.
Between grid operator instructions and negative‑price hours, output is curtailed several times a month. How much each site lost, and why, is never worked out.
How far off schedule were we last week, by site?
How many hours of curtailment did we have in September?
Which inverters at solar plant 2 are producing less than their neighbours?
At what times of day do we pay the most in imbalances?
Which turbines can be stopped in the next low-wind window?
AI cross‑checks SCADA, the weather forecast and wholesale market prices to revise the expected output of each site, and reads the O&M history to anticipate the next fault.
Forecast by site and by hour, with the gap in MWh, revised whenever a new weather forecast comes in.
Temperatures and vibrations of each turbine compared with its neighbours in the same wind conditions.
Curtailment hours by site, split between grid operator instructions and negative‑price hours.
Work orders raised from the alerts and booked for the hours with the least wind, with O&M approval.
Illustrative figures.
We connect to the systems you already have, without replacing them, and you decide which data each agent can read.
ERP, CRM, email and documents stay where they are, and nobody has to move to a new system.
Brings together what is scattered today and finds what does not add up.
Every sensitive action goes to whoever has the authority to approve it.
Works inside your team's systems and records where every decision came from.
We start with the site that has the largest imbalances and compare both forecasts hour by hour. Once the new one proves more accurate, it starts feeding the proposals to the trading desk.
We map the operation and the data and choose what reaches production first.
We build in the tools you already use and put the system to work on real cases.
Your team takes the system over and we choose the next process together.
Yes. The forecast you already receive comes in as one more source, alongside the weather and actual output from SCADA. The model learns where that forecast tends to miss at each site and corrects it through the day.
Through whatever your SCADA offers: an API, read access to the historical database or scheduled exports of the 10-minute data. The connection is read‑only, and nothing is written to the turbine or inverter control systems.
Yes, with a different starting point. For a supplier, we begin with the demand forecast for the customer portfolio and the bills based on estimated readings. For a grid operator, with the incidents that keep recurring in the same area.
Your team. The system proposes the intraday purchase or sale and the maintenance window, and nothing goes out without approval from someone on the trading desk or in O&M, with a record of who gave it.
In 30 minutes we look at which hours and which sites account for most of the cost, and what it would take to forecast it.
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