Vaisala, a global leader in environmental and industrial measurement, has released the results of the world’s largest solar dataset validation study undertaken to date. This extensive verification process, plays a critical role in ensuring that solar resource data stays accurate and consistent across the globe. In turn, it will support the efforts of international solar developers as the industry expands into important emerging markets within Asia, Africa and Latin America.
The most recent validation paper compares observational data from nearly 200 ground stations across six continents with satellite derived irradiance records from five different versions of Vaisala’s proprietary global solar dataset. The results of the study indicate that across the globe Vaisala’s values for global horizontal irradiance (or GHI, the key variable for PV projects) have a standard deviation of bias error, more commonly referred to as the uncertainty, of 4.4-4.9% depending on the version of the dataset.
To conduct a fair and unbiased study, Vaisala reserves ground station data exclusively for validation purposes and never uses data from these stations to calibrate or enhance the accuracy of its solar resource information. This provides users of the dataset an accurate estimate of how the data will perform at their project locations.
Keeping satellite resource information up-to-date
Due to sparse direct observation networks and the high uncertainty associated with publicly available solar resource information, satellite processing methodologies, which generate long-term, hourly records of solar resources specific to a project location, have become the standard in pre-construction energy assessment practices for utility-scale development.
Given the importance of this data in bringing projects to fruition, Vaisala actively maintains and updates multiple versions of its dataset to give solar project developers and financiers greater confidence and a more thorough understanding of local resource variability across the globe.
Accounting for variations in local conditions
“Vaisala has been working actively within the energy industry since 2009 to quantify and reduce solar resource uncertainty worldwide,” said Gwendalyn Bender, Head of Solar Services at Vaisala. “Over the years, we have seen how significantly local factors, such as pollution, dust, or seasonal variation, can influence the accuracy of solar resource information – and thus a project’s future solar power generation. In India, for instance, aerosol levels have changed dramatically over the past five years.
“These regional differences are often better captured by using a different aerosol or turbidity input or by employing a different irradiance model. By providing multiple, validated datasets that are processed consistently across the globe, our clients can now compare the results to find the solar data source that best fits local conditions.”
Bender further commented, “Understanding the reliability of resource data through validation is particularly imperative as solar development grows within emerging markets. For example, no other solar data provider has validated the accuracy of its resource information against actual ground observations within the important and thriving Mexican solar market.”
Choosing the most representative dataset
All five of Vaisala’s datasets are available online through its Solar Time Series Tools allowing developers and independent engineers to easily compare different datasets, understand the uncertainty associated with solar resource at a project location and quickly download the most representative solar resource time series information.
News item from Vaisala
via Solar Power World http://bit.ly/2flSfQL
April 27, 2017 at 09:10AM