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By Ioana Patringenaru, UCSD, July 2011 - Those solar panels on top of the roof aren't just providing clean power; they are cooling the house or workplace, too, according to a team of researchers led by Jan Kleissl, a professor of environmental engineering at the UC San Diego Jacobs School of Engineering. In a study in an upcoming issue of the journal Solar Energy, Kleissl and his team published what they believe are the first peer-reviewed measurements of the cooling benefits provided by solar photovoltaic panels. Using thermal imaging, researchers determined that during the day, a building's ceiling was 5 degrees Fahrenheit cooler under solar panels than under an exposed roof. At night, the panels help hold heat in, reducing heating costs in the winter. "Talk about positive side-effects," said Kleissl. As solar panels sprout on an increasing number of residential and commercial roofs, it becomes more important to consider their impact on buildings' total energy costs, Kleissl said. His team determined that the amount saved on cooling the building amounted to getting a 5 percent discount on the solar panels' price, over the panels' lifetime. Or to put it another way, savings in cooling costs amounted to selling 5 percent more solar energy to the grid than the panels are actually producing— for the building researchers studied. (Scroll to bottom for additional resources)
Data for the study was gathered over three days in April on the roof of the Powell Structural Systems Laboratory at the Jacobs School of Engineering with a thermal infrared camera. The building is equipped with tilted solar panels and solar panels that are flush with the roof. Some portions of the roof are not covered by panels.
The panels essentially act as roof shades, said Anthony Dominguez, the graduate student lead on the project. Rather than the sun beating down onto the roof, which causes heat to be pushed through the roof and inside the ceiling of the building, photovoltaic panels take the solar beating.
Then much of the heat is removed by wind blowing between the panels and the roof. The benefits are greater if there is an open gap where air can circulate between the building and the solar panel, so tilted panels provide more cooling. Also, the more efficient the solar panels, the bigger the cooling effect, said Kleissl. For the building researchers analyzed, the panels reduced the amount of heat reaching the roof by about 38 percent.
Although the measurements took place over a limited period of time, Kleissl said he is confident his team developed a model that allows them to extrapolate their findings to predict cooling effects throughout the year.
For example, in winter, the panels would keep the sun from heating up the building. But at night, they would also keep in whatever heat accumulated inside. For an area like San Diego, the two effects essentially cancel each other out, Kleissl said.
The idea for the study came about when Kleissl, Dominguez and a group of undergraduate students were preparing for an upcoming conference. They decided the undergraduates should take pictures of Powell's roof with a thermal infrared camera. The data confirmed the team's suspicion that the solar panels were indeed cooling the roof, and the building's ceiling as well.
"There are more efficient ways to passively cool buildings, such as reflective roof membranes," said Kleissl. "But, if you are considering installing solar photovoltaic, depending on your roof thermal properties, you can expect a large reduction in the amount of energy you use to cool your residence or business."
If additional funding became available, Kleissl said his team could develop a calculator that people could use to predict the cooling effect on their own roof and in their own climate-specific area. To further increase the accuracy of their models, researchers also could compare two climate-controlled, identical buildings in the same neighborhood, one with solar panels, the other without.
The following story about related research at UCSD was adapted by ScienceDaily staff from materials provided by University of California - San Diego. The original article was written by Ioana Patringenaru.
Researchers Create Tool to Put the Lid on Solar Power Fluctuations
ScienceDaily (June 22, 2011) — How does the power output from solar panels fluctuate when the clouds roll in? And can researchers predict these fluctuations? UC San Diego Professor Jan Kleissl and Matthew Lave, a Ph.D. student in the Department of Mechanical and Aerospace Engineering at the Jacobs School, have found the answer to these questions. They also have developed a software program that allows power grid managers to easily predict fluctuations in the solar grid caused by changes in the cloud cover. The program uses a solar variability law Lave discovered. WATCH ANIMATION that shows how solar output fluctuates as cloud cover changes on the UC San Diego campus.
The finding comes at a time when the Obama administration is pushing for the creation of a smart power grid throughout the nation. The improved grid would allow for better use of renewable power sources, including wind and solar.
Also, more utilities have been increasing the amount of renewable energy sources they use to power homes and businesses. For example, Southern California Edison reported this month that it is adding more large-scale solar power plants to its grid and retooling its distribution system to accommodate the power fluctuations that will follow.
Kleissl and Lave's finding could have a dramatic impact on the amount of solar power allowed to feed into the grid. Right now, because of concerns over variability in power output, the amount of solar power flowing in the grid at residential peak demand times -- your typical sunny weekend afternoon in Southern California, say -- is limited to 15 percent before utilities are required to perform additional studies. As operators are able to better predict a photovoltaic system's variability, they will be able to increase this limit. In California, a law signed by Gov. Jerry Brown in April 2011 requires all electricity retailers in the state, including publicly owned utilities, to generate 33 percent of their power sales from renewable energy sources by 2020.
Incidentally, Kleissl and Lave's research shows that the amount of solar variability can also be reduced by installing smaller solar panel arrays in multiple locations rather than building bigger arrays in just one spot, since a cloud covering one panel is less likely to cover the other panels, Lave said.
"The distance between arrays is key," he said.
The variability in the output of photovoltaic power systems has long been a source of great concern for utility operators worldwide. But Kleissl and Lave found that variability for large photovoltaic systems is much smaller than previously thought. It also can be modeled accurately, and easily, based on measurements from just a single weather station. Kleissl presented the paper, titled 'Modeling Solar Variability Effects on Power Plants,' this week at the National Renewable Energy Laboratory in Golden, Colo.
His findings are based on analysis of one year's worth of data from the UC San Diego solar grid -- the most monitored grid in the nation, with 16 weather stations and 5,900 solar panels totaling 1.2 megawatts in output. Lave looked at variations in the amount of solar radiation the weather stations were receiving for intervals as short as a second. The amount of radiation correlates with the amount of power the panels produce.
Based on these observations, he found that when the distance between weather stations is divided by the time frame for the change in power output, a solar variability law ensues. This operation was inspired by a presentation by Clean Power Research, a Napa-based company, at the Department of Energy -- California Public Utility Commission High Penetration Solar forum hosted by UC San Diego in March 2011. "For any pair of stations at any time horizon, this variability law is applicable" says Lave. In other words, the law can be applied to any configuration of photovoltaic systems on an electric grid to quantify the system's variability for any given time frame.
But Lave didn't stop there. He developed an easy-to-use interface in MATLAB that allows grid planners and operators to simulate the variability of photovoltaic systems. Data can be input as a text file, but the interface also allows users to simply draw a polygon around each system on a satellite Google Map. Based on solar radiation measurements at a single sensor on a given day, the model calculates the variability in total output across all systems.
"It is as easy as painting by numbers," said Kleissl. "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."
Kleissl said he anticipates this tool will be useful to figure out whether problems in voltage fluctuation may occur in power feeder systems with a large amount of photovoltaic arrays. At this point, the solar installations on almost all feeders are still far below the capacity that would cause any major issues. But as the United States moves to affordable solar systems producing energy at lower costs through the Department of Energy's SunShot initiative and continued robust growth in installations, this will change. That's when the tool developed by Lave and Kleissl could become key.
The model development was sponsored by DOE's High PV Penetration Program grant.
While the tool is being prepared for final public release, the authors would be happy to consider requests by third parties that can provide PV system location and size data to run the tool.