Predicted Power Forecasts

PredPowerTopSTEVE

As more and more solar PV is being introduced onto the grid, professionals who manage power distribution are challenged to integrate solar energy resources that are difficult to predict. These professionals rely on weather forecasts to balance production and consumption, ensuring they can meet customer demands while avoiding costly energy purchases on the spot market. Efficient production and distribution of solar power resources advance PV technology by helping it achieve cost parity in more markets.

Now PV asset managers have a new source for more accurate localized power production forecasts, based on breakthrough technology that provides 5-day hourly forecasts for available sunlight coupled with the AlsoEnergy PV Production Model. Accurate and detailed Predicted Power Forecasts will benefit solar asset managers, especially where systems are tied to electrical distribution networks. This feature is being brought to market in partnership with Global Weather Corporation (GWC), providers of the most accurate weather forecasts in the commercial marketplace.

AlsoEnergy will integrate GWC virtual weather data into their two lines of solar monitoring software, PowerTrack and DECK Monitoring. From our CEO Robert Schaefer:  “We are excited to introduce this technology to our clients. This is the best virtual weather service we have ever seen in the solar marketplace, and the first opportunity to see detailed long-term forecasts for power and weather.”

SolarSight Forecast

SS4cast

Adding SolarSight Forecast provides users with 5-day predicted power forecasts (hourly granularity) customized to the specs of each system. Utility and distributed solar customers can use this feature to predict and manage energy output and to minimize energy costs.

Predicted Power Forecasts are calculated by combining localized virtual weather forecasts with AlsoEnergy production modeling features. Because this technology works with the performance models you have already established in our software, your predicted power forecasts will be customized to the unique specs of your array. Data sets feature hourly granularity, so distributed solar managers can plan solar generation even during rapidly changing weather patterns.

Users may also choose to add one or both optional SolarSight packages, which add precipitation to the data stream. More importantly, the SolarSight packages integrate virtual weather data with analytic suite software tools, giving you all the same functionality you would expect from an on-site weather station.

SolarSight Forecast is available for AlsoEnergy customers with a monthly subscription plan.

Predicted Power Calculations

Users who choose SolarSight Forecast will get access to 5-day predicted power forecasts customized to their system location and design. How does it work?

The DICast technology used by GWC calculates hourly predictions for a huge range of weather variables, including cloud cover and atmospheric particles that diminish available sunlight. These numerical models are used to calculate localized Global Horizontal Irradiance (GHI) predictions for any location in the world. Accuracy has been verified by comparison to observations. The line graph at right shows forecast error statistics for a 72-hour period, illustrating GWC’s reduction in forecast error (light blue line) as compared to U.S. and Canada weather service models.

This accurate GHI data is fully integrated with the performance modeling features in AlsoEnergy software, so it can be used to generate predicted performance baselines in the same way that irradiance data from on-site weather stations generates real-time baseline values.

This technology takes full advantage of the performance modeling capabilities of our software platform, including compatibility with PVsyst models and multiple inverter modules, as well as other system variables you may have designated in the software (panel tilt and azimuth, shading modules, etc). Results are further fine-tuned using virtual weather data for atmospheric and module temperature.

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GHI forecast average error statistics (in W/m2) by model (DICast is light blue line)