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EPRI Tool Helps Utilities Prepare for Influx of Solar

These days, evidence of the rapid transformation of the electric power system is anything but abstract. GTM Research and the Solar Energy Industries Association (SEIA) report the installation of more than 4,000 megawatts of solar photovoltaic (PV) capacity in the United States in the third quarter of 2016—a nearly 200% increase compared with third quarter in 2015.

To help distribution grid operators accommodate this growth safely, reliably, and efficiently, EPRI and eight member utilities developed a tool that can forecast residential PV adoption in their service territories over the next 10 years. Numerous models can forecast market penetration of products and technologies, but until now none have been PV-specific.

“If you have good forecasts for the timing, location, and speed of PV adoption on particular circuits and can estimate the circuits’ hosting capacity, you can determine how quickly you’ll need to upgrade them to accommodate the PV or whether you can defer investment based on the PV’s ability to serve load growth,” said EPRI Principal Project Manager Nadav Enbar, who helped develop the tool.

With a better understanding of PV adoption rates, utility planners can consider such options as incentives for installations on circuits that can handle the resulting increased two-way power flows.

Building a Forecasting Tool

EPRI used a research approach known as a discrete choice experiment to develop the tool. Researchers identified solar installation attributes that influence consumers’ decisions, including type of financing, location on a utility customer’s roof or community site, greenhouse gas emissions reduction, and cost savings.

The attributes were tested with a focus group and then used to develop questions for surveys administered to more than 2,500 customers in the service territories of the eight participating utilities. The survey’s 28 questions included basic queries about income and residence size along with various solar options. The results were used to build a “choice model” for determining the combinations of attributes likely to drive customer preferences. The PV forecast adoption tool is based on this model.

“We would like to engage other utilities, survey their service areas, and use the results to make the model more robust.”

“By pairing the model with ZIP Code–level demographic data from the U.S. Census Bureau as well as historical adoption data, we can also look at how demographics impact someone’s willingness to purchase a solar system,” said EPRI Senior Project Engineer Steven Coley.

The forecast tool also factors in falling solar prices. “We can get a sense of people’s willingness to pay for solar given a set of attributes,” said Coley, who worked on the tool. “You can vary the cost in the future and see how that willingness changes.”

Improving and Expanding the Forecasts

The eight participating utilities will be the first to use the tool, which incorporates preferences and demographic data from their customers. Based on estimated annual solar-related costs and savings that PV provides for their residential customers, the utilities can determine the likely number, timing, and location of new solar installations, through direct purchase or lease, or as part of a community solar project.

“Based on user-defined costs, savings, and other inputs, the tool can output the number of customers in each ZIP Code that are likely to adopt solar each year,” said Enbar.

After refining the tool based on feedback from these utilities, EPRI in 2017 will release a more generic version for other utilities.

“The generic version will incorporate the same data on customer preferences as the current tool, but will use statewide demographic information rather than ZIP Code–level data for more general solar growth forecasts,” said Enbar. “We would like to engage other utilities, survey their service areas, and use the results to make the model more robust.”

Another potential refinement is to incorporate market data linked to why people adopt solar. “There’s an opportunity to make the tool more robust by supplementing stated customer preferences for potential purchases with data on drivers for actual purchases,” said Coley.

Similar tools may also be developed to forecast the adoption of commercial PV and electric vehicles.

EPRI Technical Experts:

Nadav Enbar, Steven Coley