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Solar data services… in the cloud
We built a new approach to solar forecasting and modeling technology from the ground up, using the latest in weather satellite imagery, machine learning, computer vision and big databases. We crunch more than 600 million new forecasts every hour in a cloud-based environment on AWS and provide real-time access to our data via API. Use the API Toolkit to access nearly 20 years of historical data, including TMY files.
Historical and TMY Data
- Low uncertainty, zero bias, bankable dataset
- Independent validation & global coverage
- High resolution data: Up to 5 minute / 90 metre resolution
- PV modelling software integration (PVSyst, SAM, TMY3, CSV)
- Solar irradiance (GHI, DNI, DHI)
- Weather (Temp, Wind, Humidity, Snow, etc)
- Includes aerosol impacts (tracking of smoke, dust, haze)
Live and Forecast Data
- Solar irradiance data (GHI, DNI, Diffuse)
- Weather (Temp, Wind, Humidity, Snow, etc)
- PV power modelling (Rooftop or Utility Scale)
- Fully-global coverage
- Rapid update (new forecasting data every 5-15 minutes)
- Proprietary cloud & aerosol detection (tracking smoke, dust, haze)
- Probabilistic forecasting outputs
- Real-time data through to 14 days ahead at 5, 10, 15, 30 & 60 minute resolution
- Delivered via REST API (download CSV or JSON)
Learn more about our data
Latest Posts
Evaluating accuracy III: PV power data
Evaluating PV Power models is essential to understand how your model processes data and considers PV Power losses. Here is a detailed guide to help you assess a forecast dataset.
Evaluating accuracy II: Forecast irradiance data
Evaluating forecast irradiance data is essential in ensuring that you're using a reliable data to effectively design and operate your solar assets. Here is a detailed guide to help you assess a forecast dataset.
Evaluating accuracy I: Satellite-derived irradiance data
Evaluating Accuracy is essential when selecting a solar data provider, make sure you're completing the right level of validation for your needs, and find easy solutions to the challenges of data validation.
