How Integrating Sky Images and Global Solar Irradiance Improves Solar Forecasting Accuracy

Solar forecasting is the process of predicting the amount of solar energy that will be produced over a certain period of time. This information is essential for optimizing the operation of solar power plants and integrating them into the grid.

Two important inputs to solar forecasting are sky images and global solar irradiance (GHI) measurements. Sky images can be used to identify cloud cover and other atmospheric conditions that can affect solar irradiance. GHI measurements provide a measure of the total solar energy received on a horizontal surface at ground level.

By integrating sky images and GHI measurements into solar forecasting algorithms, researchers are able to improve the accuracy of predictions. This can lead to significant economic benefits for solar power plant operators and grid operators.

How sky images and GHI measurements are used in solar forecasting

Sky images can be used to extract a variety of features that are relevant to solar forecasting, such as cloud cover, cloud type, and cloud height. These features can then be used as input to machine learning models to predict solar irradiance.

GHI measurements can be used to provide a baseline estimate of solar irradiance. This baseline can then be adjusted based on the information extracted from sky images to produce a more accurate prediction.

Benefits of integrating sky images and GHI measurements into solar forecasting algorithms

Integrating sky images and GHI measurements into solar forecasting algorithms can lead to a number of benefits, including:

• Improved accuracy of solar irradiance predictions
• Reduced uncertainty in solar power production
• Increased efficiency of solar power plant operation
• Improved integration of solar power into the grid

Examples of how sky images and GHI measurements are being used in solar forecasting

A number of research groups and companies are developing and deploying solar forecasting algorithms that integrate sky images and GHI measurements. Some examples include:

• The National Renewable Energy Laboratory (NREL) has developed a solar forecasting algorithm called the Solar Radiation Research Laboratory (SRRL) model. The SRRL model uses sky images and GHI measurements to produce solar irradiance predictions for the next hour and the next day.
• The company Solcast provides solar forecasting services to a variety of customers, including solar power plant operators, grid operators, and energy traders. Solcast’s solar forecasting algorithms integrate sky images, GHI measurements, and other data sources to produce high-accuracy predictions of solar irradiance.

The integration of sky images and GHI measurements into solar forecasting algorithms is a promising way to improve the accuracy of solar irradiance predictions. This can lead to a number of benefits, including improved efficiency of solar power plant operation, reduced uncertainty in solar power production, and improved integration of solar power into the grid.

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