The unpredictability in the output of solar power systems has long been of great concern to power operators worldwide. However, Professor Jan Kleissl and Ph.D. student Matthew Lave created a computer program that allows operators to easily predict fluctuations in the power grid.
The researchers developed the program after discovering a new "solar variability law." This was made based on an analysis of one year's worth of data from the university's solar grid.
This solar variability law is applicable to any configuration of photovoltaic systems on an electric grid to quantify the system's variability for any given timeframe.
The program can predict how fluctuation through weather conditions such as clouds passing over the sun can affect the power output of solar panels.
Mr. Lave monitored the variations in the amount of solar radiation that the weather stations received for short intervals. He found out that the amount of radiation showed a direct relationship to the amount of power that the panels produce.
In general, the researchers found that the key to reducing the fluctuations is the distance between the panels. With smaller solar power systems, the cloud may cover one panel but may less likely cover the others.
They suggested that in order to reduce fluctuations in solar power due to cloud cover, it is better to build several smaller solar energy systems rather than building a single large solar farm in one area.
The researchers then incorporated the solar variability law into a software program that allows grid planners and operators to simulate the variability of their systems.
Currently, the amount of solar power allowed in a United States residential grid is capped at 15 percent. However, the application of solar variability programs to PV systems can lift the lid on solar power use.
The development of the technology is part of the Solar Energy Technologies Program funded by the Department of Energy. (K.A. Mariano)
source: Apec-vc Korea
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