The rooftop solar indus­try in the US has expe­ri­enced dra­matic growth, roughly 50% per year since 2012 along with steadily falling prices. One study at NREL esti­mates the national rooftop solar poten­tial to be 1,432 TWh of annual energy gen­er­a­tion, which equates to 39% of total national electric-​​sector sales. Despite this vast poten­tial, last year dis­trib­uted solar pro­duced roughly 24 TWh (less than 1.7% of the national rooftop solar poten­tial). In order to best plan for increased deploy­ment of rooftop solar, poten­tial rooftop gen­er­a­tion data at high spa­tial and tem­po­ral res­o­lu­tion are needed. In this pre­sen­ta­tion, we will dis­cuss the use of Google Project Sunroof’s data and NREL’s Sys­tem Advi­sory Model to cal­cu­late hourly time-​​series data at the zip code-​​level for both exist­ing and poten­tial rooftop PV instal­la­tions. We will dis­cuss chal­lenges to the model assump­tions and con­clude with oppor­tu­ni­ties for fur­ther development.

YongJun Song is pas­sion­ate about the neces­sity of sus­tain­able design in today’s global econ­omy. With his per­sonal expe­ri­ence of the issues present in sus­tain­able design and his edu­ca­tion at Cal, he has made it his pur­pose to con­tribute to the sus­tain­able energy indus­try with the ulti­mate goal of pro­vid­ing energy to the pop­u­la­tion using on-​​site renew­able and location-​​appropriate energy sources. Through his research expe­ri­ence at the Renew­able & Appro­pri­ate Energy Lab­o­ra­tory (RAEL), he devel­oped an inter­est in inves­ti­gat­ing the dif­fer­ent ways sus­tain­able energy sys­tems could be inter­wo­ven with geo­graph­i­cal, eco­nom­i­cal, and envi­ron­men­tal fea­tures. In par­tic­u­lar, as a con­tin­u­a­tion of his research at RAEL, he is inter­ested in quan­ti­ta­tively ana­lyz­ing (1) the poten­tial for solar energy to out­door park­ing lots and (2) the trans­for­ma­tion of the con­ven­tional grid into a dis­trib­uted grid to expand access to elec­tric car charg­ing sta­tions. Song is a B.A. can­di­date in Sus­tain­able Envi­ron­men­tal Design, pur­su­ing a minor in Geospa­tial Infor­ma­tion Sci­ence. In his per­sonal time, he likes to explore nature, take pho­tos, and ride a horse.

Jacky Zhu is a 3rd-​​year under­grad­u­ate stu­dent at UC Berke­ley major­ing in Elec­tri­cal Engi­neer­ing and Com­puter Sci­ences. He joined RAEL in Spring 2017 and has worked under Pro­fes­sors Daniel Kam­men and Deb­o­rah Sunter on the “City-​​Integrated PV for Urban Trans­porta­tion”, “Inclu­sive Green Growth met­rics”, and “SWITCH USA” projects. His main inter­ests lie in machine learn­ing and data sci­ence. With the vast amounts of data in the renew­able energy field, he hopes to imple­ment data-​​driven meth­ods to opti­mize renew­able energy deploy­ment. He pre­vi­ously interned as a research ana­lyst at SunPower.