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MIT develops new solar resource map to help Cambridge go solar

MIT Screenshot of Cambridge Solar MapMIT is making it easier for the people of Cambridge to go solar, thanks to a new solar mapping tool that it developed. Residents, businesses and others in Cambridge can look up addresses throughout the town to determine the potential of rooftop solar at the location, including estimated system cost, payback and return on investment. The tool may be the most advanced solar resource estimator thus far developed.

In addition to looking at other data including GIS information, insolation (solar radiation) and weather information, in developing the tool, MIT’s Sustainable Design Lab and partner Modern Development Studio LLC used additional tools and metrics. “We used a typical meteorological year from Logan Airport composed out of 12 years’ worth of measured solar radiation data,” said MIT Associate Professor Christoph Reinhart, who heads the department.

“The data set consist of typical hourly direct and diffuse radiation data plus ambient temperature. We then build a 3D model of the city using LiDAR data, combined our 3D model with the hourly radiation data set and derived via raytracing the amount of solar radiation shining on every rooftop in Cambridge using a 5’ by 5’ sensor point grid,” Reinhart said. The 3D modeling allowed the map to interpret roof pitches and add them into the equation. Together, they, “Yielded hourly electricity yield form PV panels installed on different roof surfaces,”Reinhart said.

The tool also accounted for hourly temperatures throughout a year in its calculations. Since solar cells are less efficient when they heat up it reduces their energy production even though they get more sunlight—something that’s not always accounted for in other mapping tools.

In addition to showing users how much a system is anticipated to cost for a given location, including incentives, and revenue the system will generate—both in terms of kilowatt hours and solar renewable energy credits (SREC) it also shows anticipated return on investment. The return on investment estimator calculates how long it will take a system to produce a return and compares the percentage of ROI to the Dow Jones Index, Gold and U.S. Treasury Bonds—guess what? Solar tends to produce higher ROIs.

The tool does not discuss different financing options. “The city is maintaining the map and does not endorse any particular financing schemes,” Reinhart said. In addition it doesn’t maintain a list of local installers, which users can find via Cambridge.

The model does show data for roughly 17,000 buildings in Cambridge using colors to illustrate which parts of each roof is most to least suited for solar. If solar was installed on all locations considered good and excellent, Cambridge could generate about a third of its electricity needs for about $2.8 billion, according to MIT.

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