SteadyMet
Solar forecasts for the coming days
ABOUT
Forecasts based on meteorological models for day-ahead solar forecasting needs
SteadyMet can be configured at very high resolution using the Weather Research and Forecasting (WRF) model, providing highly accurate forecasts at local scale. Steadysun is able to implement and optimize this model anywhere in the world to meet the need of high-quality day-ahead forecasts.
Download the SteadyMet product sheet
Update frequency
1 min
Forecast time-step
Power, GHI, DNI, DHI, GTI, Temperature, Wind, etc
Available parameters
Site, Portfolio, City, Region or Country
Coverage
PV, Trackers, Bifacial, CSP
Technology
API, SFTP, etc.
Data delivery
P10, P20,…, P80, P90
Confidence levels
KEY BENEFITS
WORLDWIDE COVERAGE
Thanks to a large number of global and regional NWP data from several weather services.
BEST-IN-CLASS SOLUTION
An approach combining ensemble predictions from the leading weather models, real-time on-site measurements and cutting-edge technologies to offer accurate probabilistic forecasts.
RELEVANT FOR MICROCLIMATES
TAILORED OUTPUTS
CUSTOMERS NEEDS
Our solutions are tailored to meet your solar business needs.
METHODOLOGY
Weather model’s outputs of interest (solar radiation, temperature, wind, etc.) are then optimized (step 3), by using production/irradiance observations, to take into account local phenomena, and by leveraging artificial intelligence technologies.
Ready-to-use forecasts, in a customized format, are then disseminated (step 4) through our proprietary web interface, csv files delivered via (S)FTP platforms or API.
DATA ACQUISITION
> From several external and internal sources.
> Global and Regional Numerical Weather Prediction (NWP) models.
> Numerous parameters (clouds, radiation, temperature, wind, aerosols, etc.)
MODELING
> Accurate estimation of clear sky conditions using real-time aerosols prediction.
> PV modeling based on physical models and plant features.
> High-resolution topographical corrections (down to 90m).
> Probabilistic forecasting using physical and statistical approaches.
OPTIMIZATION
> Continuous accuracy improvements using state-of-the-art machine learning techniques.
> To take into account local weather phenomena and power plants’ behavior.
DELIVERY
> Customized format (csv, txt, etc.).
> Dedicated and secured web interfaces (visualization, data analytics and warnings).
> Forecast performance monitoring.
Step 1: DATA ACQUISITION
> Global and Regional Numerical Weather Prediction (NWP) models.
> Numerous parameters (clouds, radiation, temperature, wind, aerosols, etc.)
Step 2: MODELING
> Accurate estimation of clear sky conditions using real-time aerosols prediction.
> PV modeling based on physical models and plant features.
> High-resolution topographical corrections (down to 90m).
> Probabilistic forecasting using physical and statistical approaches.
Step 3: OPTIMIZATION
> Continuous accuracy improvements using state-of-the-art machine learning techniques.
> To take into account local weather phenomena and power plants’ behavior.
Step 4: DELIVERY
> Customized format (csv, txt, etc.).
> Dedicated and secured web interfaces (visualization, data analytics and warnings).
> Forecast performance monitoring.
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