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Lab studies effects of clouds on solar plants

ALBUQUERQUE, N.M. — Sandia National Laboratories engineers have been studying the most effective ways to use solar photovoltaic (PV) arrays that are relatively easy to install, have relatively small maintenance costs and can run unassisted for decades.

But clouds could dim industry growth: What happens when they cover part of a solar PV array and cause a dip in output, how big is the dip and how can a utility company compensate for it?

Sandia, in a news release, says researcher Matt Lave has been working to understand that drawback and determine just how much clouds can affect solar-power plant output. Typically, sunlight is measured using a single irradiance point sensor, which correlates nicely to a single PV panel. But that doesn’t translate to a large PV power plant.

“If a cloud passes over, it might cover one panel, but other panels aren’t affected,” Lave said. “So if you use the single point sensor to represent the variability of the whole power plant, you will significantly overestimate the variability.”

Lave is working with Sandia engineer Josh Stein and University of California-San Diego professor of environmental engineering Jan Kleissl to develop a “wavelet variability model” to get a more accurate picture of how clouds affect PV power plants.

The model uses data from a point sensor and scales it up to accurately represent the entire power plant. The model uses measurements from an irradiance point sensor, the power plant footprint – the arrangement and number of PV modules in the plant – and the daily local cloud speed to estimate the output of a power plant.

The model is useful for estimating how much energy must be stored to make up for cloud-caused fluctuations, Sandia said.

The variability is a concern for grid operators as unanticipated changes in PV plant output can strain the electric grid.

The team recently published a book chapter in “Solar Energy Forecasting and Resource Assessment.” Chapter 7, “Quantifying and Simulating Solar-Plant Variability using Irradiance Data,” offers metrics to characterize and simulate the variability of solar power plant output.

This work is supported by the Department of Energy’s SunShot Initiative, a national effort to make solar energy cost-competitive with traditional sources of energy by 2020 and greatly increase how much solar energy safely and cost-effectively goes to the electric grid.

The research is designed to help grid operators solve variable short-term power-generation problems, Lave said.


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