With more solar energy coming onto the grid every day, how can you successfully integrate and take advantage of this intermittent resource? Vaisala's solar forecast offers a competitive edge in effectively managing risk at your project and across your energy portfolio.
See Also - Regional Solar Energy Forecasting
Vaisala's forecast system is based on the most advanced numerical weather prediction modeling techniques. It statistically integrates on-site data to calibrate forecast predictions to a project site's distinct geography and climate. When long-term ground observations are unavailable we use nearly 20 years of hourly site data from our global solar dataset to provide a reliable and accurate solar production forecast. Our methodology accounts for localized characteristics such as clouds influenced by complex terrain, coastal effects, and monsoon.
Developed and Tested In The Real World
Vaisala's forecast was created through a partnership with one of the Southwest's largest utilities and solar energy producers. The resulting system was piloted, tested, and improved based on performance in real world applications at actual utility-scale solar projects.
In addition to industry leading accuracy, Vaisala's solar forecast also offers ease of use. Forecasts are delivered through a customizable dashboard, displaying site-specific conditions with easily interpreted graphics. Users can also download the day-ahead irradiance and power forecasts as data files and access historical forecast information.
Forecasting information is made available via a client-specific dashboard interface accompanied by data files in an easily integrated CSV file format. Data files can also be accessed via API.
Vaisala developed our solar forecast using the most physically robust technique to provide accurate irradiance and power forecasts specific to a solar project's unique environment. The numerical weather prediction model Vaisala employs is an open source model continually updated and improved upon by the international atmospheric science and research community.
In the forecast model initialization process, we statistically integrate historical observations provided by the client or hourly, high-resolution (3km), satellite derived solar data, which are well calibrated to ground measurements. This statistical process is called model output statistics (or MOS) and significantly reduces forecast error and bias. In addition, Vaisala validates the solar forecast using our global solar dataset, which is based on over a decade of actual, high-resolution visible satellite imagery observations.
To provide solar forecasting, Vaisala must be supplied with all the meta data for your project such as: time zone, project location, and panel information. For power forecasting the client must provide historical irradiance, power production data, or a power conversion formula. Historical data is not required for GHI forecasting.
Features • Solar Forecast Tools - MOS-corrected day-ahead GHI or power forecast with downloadable forecast data files • Rewind Tool allows you to compare the current forecast with previous predictions • API available for faster integration of downloadable forecast data into your internal analysis tools and programming software • Customizable dashboard interface • Guaranteed 24/7 availability • Frequency - The forecast is updated every 6 hours, provides hourly predictions, and projects 60 hours into the future • Security - Easily set your own permissions system for access to forecast information with unique usernames and passwords. In addition, Vaisala provides a secure password protected web host server for all data transfers
• Make more profitable decisions with accurate, custom forecasts • Our solar forecasting system combines the latest in weather and data science to deliver accuracy and reliability. By leveraging powerful atmospheric models, machine learning, and 20 years of high-quality historical information from our global dataset, we tailor each forecast to its unique local environment.
• Improve scheduling and reduce risk • Maximize solar generation and detect reduced production days in advance to better manage scheduling and integration - all while minimizing imbalance penalties and other downside risks.
• Manage your thermal and renewable energy supply portfolio • Optimize your portfolio on a daily basis, allowing more efficient management across all your generation assets.