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Engineers Calculate, Write Software for Solar Fluctuations

Technicians in front solar panel array (NREL)

(National Renewable Energy Laboratory)

A faculty-student engineering team at University of California, San Diego has developed a computer model to calculate fluctuations in the solar power grid caused by changes in cloud cover. The team of professor Jan Kleissl and Ph.D. student Matthew Lave have also written software to help power grid managers predict fluctuations in the solar grid caused by cloud cover changes.

The work of Kleissl and Lave to give power grid managers better predictive tools is well-timed. In California, a law passed and signed in April 2011 requires all electric power utilities to generate 33 percent of their power sales from renewable energy sources by 2020. Because of concerns over variability in power output, however, the amount of solar power flowing in the grid at residential peak demand times is limited to 15 percent before utilities are required to perform additional studies.

Kleissl presented his findings in a paper this week, titled “Modeling Solar Variability Effects on Power Plants,” at the National Renewable Energy Laboratory in Golden, Colorado. He and Lave found that variability for large photovoltaic systems is much smaller than previously thought, and can be modeled accurately based on measurements from a single weather station.

The engineers base their model on a year’s worth of data from the UC San Diego solar grid, with 5,900 solar panels totaling 1.2 megawatts in output. Monitoring the grid is 16 weather stations, making it the most monitored grid in the nation.

The algorithm for calculating variability in solar output turned out to be fairly straightforward. Kleissl and Lave discovered that solar variability could be modeled based on the distance between weather stations divided by the time frame for the change in power output. And they found this algorithm could be applied to any configuration of photovoltaic systems on an electric grid to quantify the system’s variability for any given time frame.

Lave then took the task one step further and wrote software that allows grid planners and operators to simulate the variability of photovoltaic systems. The software allows operators to input data directly, or locate solar panel installations on Google Maps, and simply draw a polygon around each system on the map display. The system can then calculate the variability in total solar output based on measurements from as few as one monitoring station on the grid, on a given day.

Since the amount of power generated by solar installations is still well below capacity, current demand for the model is low. With the growing number of installations and lower prices for solar arrays, however, the solar variability model and software are expected to generate considerably more interest from grid operators.

Read more: Enviro. Engineer Recalibrates Solar Panel Placement

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