Real-time irradiance
and PV production data
Live data for solar resource assessment and PV monitoring
CONTACT US
ABOUT
Real-time estimates based on satellite imagery and weather models
Real-time images are received from several geostationary meteorological satellites operated by NOAA (GOES -W, GOES -E), EUMETSAT (MSG -0°, MSG-IODC), and JMA (HIMAWARI). These providers were selected because these 5 satellites cover the whole globe at high spatio-temporal resolution - 5 to 15 minutes and 500 m to 2 km depending on the region and channel (visible/infrared). Raw satellite images provide continuous information on cloud properties (e.g., type and opacity).
In addition, several weather models are used to bring useful information on other key atmospheric constituents interacting with solar radiation (water vapor, ozone, aerosols and albedo). For instance, the Copernicus Atmosphere Monitoring Service (CAMS) global analysis and reanalysis from ECMWF provide the concentration of ozone and aerosols (e.g. dust, sea-salt, biomass-burning, sulfate).
The Global Horizontal Irradiance (GHI) in clear sky and cloudy conditions are computed independently using state-of-the-art models for Radiative Transfer, parallax correction and shadow projections. Then, separation and transposition models determine the direct (beam), diffuse and plane-of-array irradiance (DNI, DHI, GTI).
Finally, the actual PV power can be estimated using physical models accounting for detailed plant specifications (technology, layout, shading, losses, etc).
Our irradiance and PV power data is updated every 5 to 15 minutes for any location worldwide.
5 - 15 minutes
Update frequency
1 min
Data time-step
Power, GHI, DNI, DHI, GTI
Available parameters
Site, Portfolio, City, Region or Country
Coverage
PV, Trackers, Bifacial, CSP
Technology
API, SFTP, etc.
Data delivery
KEY BENEFITS
EVALUATE THE PERFORMANCE
Of individual solar assets or a portfolio
CONTINUOUS ACCURACY IMPROVEMENT
Using in-situ measurements from various observational networks around the world. Before applying machine learning, we systematically check the quality of the data. You can easily integrate your own measurements into our system to get even more accurate estimates.
WORLDWIDE COVERAGE
Real-time process of images coming from five geostationary meteorological satellites
SOLUTIONS
Plant operation
Make your solar and wind power plants more profitable. Limit penalties, maximize revenues.
Power trading & portfolio management
Optimize transactions on power markets. Reduce unbalancing costs. Manage risks.
METHODOLOGY
Step 1
Step 2
Step 3
Step 4
DATA ACQUISITION
MODELING
OPTIMIZATION
DELIVERY
From 5 geostationary satellites.
Different channels providing information on the atmosphere, clouds and aerosols.
Every 5 to 15 minutes.
Cloud detection and classification.
Accurate estimation of clear sky conditions using real-time aerosols concentration data.
Calculation of direct and diffuse irradiance components in cloudy conditions.
High-resolution topographical corrections (down to 90m).
PV modeling based on physical models and plant features.
Based on historical and/or real-time on-site measurements.
Continuous accuracy improvements using state-of-the-art machine learning techniques.
To take into account local weather phenomena and power plants’ behavior.
Flexible delivery (API, SFTP, etc..).
Customized format (csv, txt, etc.).
Dedicated and secured Steadysun’s web interfaces (visualization, data analytics and warnings).
Performance monitoring
METHODOLOGY
Step 1
DATA ACQUISITION
From 5 geostationary satellites
Different channels providing information on the atmosphere, clouds and aerosols
Every 5 to 15 minutes
Step 2
MODELING
Cloud detection and classification
Accurate estimation of clear sky conditions using real-time aerosols concentration data
Calculation of direct and diffuse irradiance components in cloudy conditions
High-resolution topographical corrections (down to 90m)
PV modeling based on physical models and plant features
Step 3
OPTIMIZATION
Based on historical and/or real-time on-site measurements
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
Flexible sending (API, SFTP, etc.)
Customized format (csv, txt, etc.)
Dedicated and secured Steadysun’s web interfaces (visualization, data analytics and warnings)
Performance monitoring
