FollowThe University of California at San Diego’s (UCSD, San Diego, California, U.S.) Jacobs School of Engineering announced that a team of its researchers has developed software to predict fluctuations in the output of solar photovoltaic (PV) plants caused by cloud cover.
The team has also presented a paper to the U.S. Department of Energy’s National Renewable Energy Laboratories (NREL, Golden, Colorado, U.S.) on its work on variability which led to the software.
The team's findings are based on data from the UCSD grid and the PV plants that supply it with electricity
“It is as easy as painting by numbers,” said UCSD Professor Jan Kleissi, describing use of the software. “In Google Maps, photovoltaics show up as dark rectangles on rooftops. Draw some polygons around them, push the button, and out comes the total variability.”
The team is composed of Professor Kleissi and Ph.D. Student Matthew Lave.
Variability smaller than previously estimated
One of the findings of Kleissi and Lave in “Modeling Solar Variability Effects on Power Plants” is that the variability of large PV plants is smaller than previously predicted.
The team states that using their software, such variability can be modeled accurately and easily from measurements at a single weather station.
Kleissi and Lave’s research also confirms that the amount of solar variability can be reduced by installing smaller PV arrays in multiple locations rather than building bigger arrays in one location.
The team’s findings are based on one year’s worth of data from the UCSD grid and its associated PV plants, with 16 weather stations and 5,900 PV modules totaling 1.2 MW in output.
Variability law based on observations of UCSD grid
Kleissi and Lave based their software on a variability law developed by Lave, which in turn is based on his observations of the UCSD grid. This variability law calculates the change in power output, based on the distance between weather stations divided by the time frame.
Using this variability law, Lave developed an interface in MATLAB that allows grid planners and operators to simulate the variability of PV systems.
Based on solar radiation measurements of a single sensor on a given day, the model calculates the variability in total output across all systems.
Research supported by DOE
The team notes that the amount of PV on almost all grid feeder systems is still far below the capacity that could cause interruptions. However, the team notes that given long-term trends, this is likely to change.
The development of this model was supported through the DOE’s High PV Penetration Program grant.
Source: solarserver
