Solar Resource Assessment
Solar Resource Assessment
Gain confidence in your solar project development and financing. Vaisala's solar resource assessments provide the most reliable record of long-term solar resource intensity and variability, particularly when on-site observations are integrated into the analysis.
Portable Document File (PDF) report and data files in an easily integrated, comma-separated value (CSV) format.
Vaisala's Solar Resource Assessments offer the most accurate long-term estimates of solar resource intensity and variability. When local measurements are available we significantly reduce the uncertainty of these estimates and increase your confidence in project performance by putting site observations into a long-term, historical context.
With experience delivering nearly 1000 assessments across 6 continents, Vaisala can provide custom reports for large-scale solar projects anywhere in the world. Our analysis includes nearly two decades of hourly time series data derived using state-of-the-art satellite modeling techniques from the 3TIER Services dataset. Each report also provides a wealth of information on the key variables of GHI (Global Horizontal Irradiance), DNI (Direct Normal Irradiance), and DIF (Diffuse Horizontal Irradiance) and their long-term variability at your site.
Our Solar Resource Assessments describe the long-term spatial and temporal characteristics of the solar resource at your location. Our team of experts choose from our 5 available algorithms to pick the solar resource data that best represents your location as compared to our extensive network of observations. The weather information provided is derived from a downscaled reanalysis dataset such as NNRP or MERRA2.
By integrating on-site observations using advanced statistical techniques, Vaisala significantly reduces error and bias and offers the most accurate assessment of your project's solar resources. In addition, we deliver long-term, hourly wind and temperature data, which can have a substantial impact on power production. This depth of information enables you to perform detailed site design, long-term financial modeling, and seek critical funding for your project. Our reports also include uncertainty and probability analysis as well as the 1-year and 10-year exceedance values typically required by financing institutions.
Global Solar Dataset
Vaisala produced the first global solar irradiance map and time series dataset at roughly three times the resolution of previous U.S. solar datasets and at thirty times the resolution of global datasets available from NASA. Based on over a decade of satellite imagery and cutting-edge technology, our uniform methodology is supported by a large scientific and research community and results in a consistent map and dataset, enabling more accurate point-to-point comparisons.
The dataset is based on actual, half-hourly, high-resolution visible satellite imagery observations via the broadband visible wavelength channel at a 2 arc minute resolution. These data have been processed to hourly GHI, DNI, and DIF values. Vaisala processes the satellite images based on a combination of in-house research and algorithms published in peer-reviewed scientific literature. These algorithms contain parameters and coefficients that are based on empirical fits to observational data. The specific satellites and length of time varies slightly by region due to differences in the availability of satellite data from region to region. See the chart below for more details.
|Western Hemisphere||GOES 8 - 14||January 1997 - last month|
|South Asia & Middle East||Meteosat 5, Meteosat 7||January 1999 - last month|
|East Asia & Oceania||GMS 5, GOES 9, MTSAT 1-2, Himari-8||December 1998 - last month|
|Europe & Africa||Meteosat 7, Meteosat 9-10||July 1998 - last month|
To develop and validate our model, Vaisala used observations from:
- Baseline Surface Radiation Networks
- National Solar Radiation Database
- Bureau of Meteorology (Australia)
- National Institute of Water and Atmospheric Research (New Zealand)
- Indian Meteorology Department
- NREL Annex II
- Linke Turbidity Database from Ecole des Mines de Paris
- National Snow and Ice Data Center (high-resolution snow dataset)
- MODIS Aerosol Optical Depth and Water Vapor Datasets