Research will soon be conducted by Clean Power Research, which develops analytic tools for the renewable energy industry, in order to determine how much cloud cover affects the performance of large solar-power arrays.
Clean Power Research will conduct the research thanks to an $852,260 grant from the California Public Utilities Commission to develop new simulations for the experiment. The grant was won as part of a program that totaled $7.65 million from the California Solar Initiative’s Research, Development, Deployment and Demonstration Program.
Clean Power Research is planning on validating its existing photovoltaic panel fleet simulations that were developed from earlier funding from the California solar installation program. CPR manufactured tools to measure power output and variability without being required to monitor the solar systems, according to the company.
“Accurate solar forecasting is critical for integrating ever-larger PV fleets into the grid, yet the expense and difficulty of obtaining this information can be very high,” said Tom Hoff, president of research and consulting at Clean Power Research. “This grant builds on our previous CSI RD&D research, allowing us to validate our PV simulation models and make them widely available through easy-to-use software tools.”
The intermittent nature of photovoltaic system’s output during different times of the day means accurate solar forecasting is vital for utilities that plan on integrating PV into their planning, scheduling and operating strategies, in order to maintain grid reliability.
The Clean Power Research project is bringing together several renewable energy companies, including the California Independent System Operator Corporation, Pacific Gas and Electric Company, Sacramento Municipal Utility and Electric Power Research Institute.
SolarAnywhere data will also be used in screening distribution feeders during the project as alternatives to the 15 percent rule and for high-fidelity solar forecasting for grid integration undertaken by UC-San Diego.
“Our analysis has shown that SolarAnywhere is one of the most accurate and highly spatially resolved solar resource datasets available,” said Jan Kleissl, UC-San Diego assistant professor of environmental engineering. “Clouds cannot hide from a satellite.”
In June 2011, Kleissl and UC-San Diego Ph.D. student Matthew Lave unveiled an easy-to-use tool that gives developers an estimate of solar variability at any given site. Their research also showed that solar variability can be reduced by placing installing smaller solar panels further apart from each other, which increases the probability that when clouds block sunlight from reaching one panel, another will be receiving rays.
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