Wind power forecasting software for asset operators

Site-level wind generation forecasts with sub-hourly precision — trained on your turbine's power curve, hub height, terrain exposure, and local wind patterns.

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What is wind power forecasting?

Wind power forecasting predicts how much electricity a specific wind asset will generate using site-level conditions like turbine parameters, terrain, wake effects, and rapidly changing weather patterns. Amperon’s models combine multiple weather sources with historical generation data, continuously updating to adapt to changing wind conditions in real time.

Amperon's wind forecasting products

Asset wind short term forecast

Horizon:

Short-term (day-ahead+)

Update frequency:

xxx

Delivery:

API, snowflake, file

Use cases:

Day-ahead bidding, generation scheduling, portfolio reporting

Short-term wind generation forecast for individual assets. Captures the nonlinear relationship between wind speed and power output — including cut-in behavior, rated power plateau, and high-wind cut-out — that linear wind-to-power estimates get wrong. Each model trained on your site's historical generation data and local wind patterns.

X.X%

MAPE for DA generation forecasts

Asset wind sub-hourly

Horizon:

Intra-day

Resolution:

Sub-hourly

Updates:

Continuous

Delivery:

API, snowflake, file

Use cases:

Curtailment management, intra-day market participation, real-time dispatch

Intra-day wind generation forecast with sub-hourly resolution. Built for wind ramp events — sudden output swings caused by front passages or directional shifts that coarser forecasts miss. Uses real-time meteorological feeds and turbine-level performance data to capture transitions as they develop, not after they've hit your output.

X

Frequency/resolution placeholder stat

Reduce wind curtailment with better forecasts

Wind ramps are faster and less predictable than solar dips. Sub-hourly forecasting gives you the lead time to act before output swings hit.

Detect ramp events before they hit

See output swings developing 30–60 minutes ahead — enough time to adjust positions and pre-stage curtailment.

Recover revenue lost  to forecast error

X% fewer unexpected curtailment events

Connect to the full market picture

Wind forecasts feed into Amperon's net demand signal for complete grid-level context.

Wind asset forecast accuracy — DA MAPE

X+

Number of wind assets forecasted

X wks

Onboarding / deploymentspeed

How it works

View integration documentation

Data ingestion

Public ISO demand data combined with 25+ years of historical weather data and real-time weather feeds. Multiple weather model sources blended for optimal accuracy.

ML Modeling

Ensemble machine learning models retrained and updated hourly as new demand and weather data arrives. Each ISO has dedicated model architectures tuned to that market's characteristics.

Output delivery

Short-term and long-term portfolio forecasts delivered via API or Snowflake. Automated day-ahead scheduling pushed directly to the ISO. Threshold alerts flag data anomalies before they impact bids.

Continuous learning loop

Models self-improve with every new data point. Accuracy compounds over time as the training dataset grows and the model adapts to shifting demand patterns, EV adoption, and electrification trends.