Solar Resource Assessment

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    Product Description

     Product Description

    Solar Resource Assessment gives you a reliable record of long-term solar resource intensity and variability, especially when on-site observations are integrated into the analysis.

    Long-Term Analysis Customized To Your Location

    As a leading innovator in atmospheric sciences, Vaisala offers custom reports for assessing large-scale solar projects anywhere in the world. Our analysis includes 16 to 18 years of hourly time series data derived using state-of-the-art satellite modeling techniques. When surface observations are available, this information is fine-tuned to the specific environmental context of your site for enhanced precision. Each report also provides a wealth of information on the key variables of GHI (Global Horizontal Irradiance), DNI (Direct Normal Irradiance), DIF (Diffuse Horizontal Irradiance), wind speed, and temperature and their long-term variability at your site.

    Secure Project Financing

    Vaisala helped pioneer the integration on-site observations incorporated into a long-term solar resource record using advanced statistical techniques. This technique significantly reduces error and bias and offers the most accurate assessment of your project’s solar resources. Other key meteorological variables, such as wind speed and temperature, are also evaluated since they can have a substantial impact on the long-term production potential of your project. 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.

    A Consistent Approach To Assessment

    As a single assessment provider with global capabilities, Vaisala allows you to make more informed decisions whether you are developing projects in California or Rajasthan. Our reports are based on a global, high-resolution solar irradiance dataset and uniform methodology, offering a consistent approach to solar assessment across the globe. Now you can make accurate site-to-site comparisons and gain a clearer picture of the risks and opportunities for every potential site in your portfolio.

     

    Vaisala’s MOS-correction bias adjustment technique that incorporates short-term observations into the long-term satellite dataset.

    Technical Overview

     Technical Overview

    Product Features

    • Temporal analysis of GHI, DNI, and DIF as well as time series data files
    • Temporal analysis of wind speed and temperature as well as time series data files
    • Uncertainty analysis
    • Exceedance probability table
    • Validation of statistically corrected irradiance time series compared to observations

    Product H​​​ighlights

    • Global coverage
    • Spatial resolution of 2 arc minutes (approximately 3km)
    • Based on over a decade of satellite data with continual updates
    • Techniques validated and developed using widely recognized datasets worldwide

    Delivery Method

    Portable Document File (PDF) report and data files in an easily integrated, comma-separated value (CSV) format.

    Methodology

     

    Vaisala's Solar Resource Assessments offer the most accurate long-term estimates of solar resource intensity and variability. When local observations are available we can increases your confidence in the production potential of your solar project by putting available site observations into long-term, historical context.

    As a leading innovator in atmospheric sciences, Vaisala offers custom reports for assessing large-scale solar projects anywhere in the world. Our analysis includes 16+ years of statistically corrected, 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 a client-specified location. Our team of solar experts will choose from our 5 available algorithms to pick the data that best represents your location of interest as compared to our extensive network of observations. The weather information will be provided 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 use a downscaled reanalysis dataset to 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 US 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 data from region to region. See the chart below for more details.

    Regions Satellites Temporal Coverage
    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:

    • SurfRad
    • 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

    Find our validation paper here.

    Customer Requirements

    In order for us to process this report, you must provide the center latitude and longitude of your solar site and one year of high quality, solar irradiance observations taken within 20​​km of the solar site.

    If you are unfamiliar with the technical terminology on this page, please visit our Glossary for more information.​​​