The funds will be used for the next phase of a project intended to develop prediction models that can be used to anticipate output from both large solar generating facilities and smaller, roof-top, distributed solar resources. The information would be passed on to operators allowing them to plan for supplemental power as needed.
The project helps advance Governor Andrew Cuomo’s (D-NY) goal of investing in renewable energy sources which will provide clean electricity to more New Yorkers.
“We need to fully understand solar output, whether rooftop or utility scale, and what the impact is of changing weather conditions, if we want to fully integrate photovoltaic power generation into system operations,” said Alan Ettlinger, director of research, technology development and innovation at NYPA.
Increasing use of solar power highlights the growing need to understand the impact of photovoltaic power generation on net system load, forecasting and planning for online generation. Solar power forecasting, up to days ahead, is required to understand how solar output may change based on cloud movement and other factors such as aerosols, pollutants and particulates.
This project will build on prior research sponsored by the U.S. Department of Energy Solar Energy Technologies Office and recently carried out by the National Center for Atmospheric Research team including Brookhaven National Laboratory. In the previous work, NCAR developed a specialized weather prediction model for day-ahead forecasting and BNL developed a sky imager system to determine the movement of clouds and their impact on power generation.
This new effort will scale up that research and determine the benefit of deploying to the wider New York state area. Activities will focus on the use of sensors and other equipment to allow for improved cloud and irradiance forecasting at several representative sites across New York State. Such networks can stitch together “snapshot” images and localized forecasting provided by individual imaging systems and thus expand forecasting capabilities over large regions and longer time horizons. The forecast network will take advantage of newly installed, enhanced MesoNet meteorological stations across the state funded by the U.S. Department of Homeland Security.
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