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.
The possibility of installing solar photovoltaics
(PV) distributed on rooftops has allowed
communities to actively participate
in molding the future of sustainable cities.
Solar PV owners also experience significant economic
benefits in the form of tax credits, rebates, and lower
net electricity consumption from utilities, leading to
lower electricity bills. It comes at no surprise that the
rooftop PV has surpassed 300 GW of installed capacity
worldwide, with trends on the rise.
In the United States, more than a million rooftops
already have solar PV systems on them, with the
numbers continuously expanding, contributing to the
achievement of bold initiatives to fully decarbonised
states’ power sectors, such as those in California, Hawaii
and New York.
Not everyone is benefiting equally from the availability of new solar energy technologies, a new study by researchers at UC Berkeley and Tufts University shows.
To access and download the paper, click here.
By combining remote sensing data from Google’s Project Sunroof with census tract information, the researchers discovered significant racial disparities in the adoption of rooftop solar photovoltaics.
“Our work illustrates that while solar can be a powerful tool for climate protection and social equity, biases and barriers to access can dramatically weaken the social benefit,” said Daniel Kammen, professor and chair of energy in the Energy and Resources Group and, professor in the Goldman School of Public Policy and director of the Renewable and Appropriate Energy Laboratory.
For households with the same median household income, black- and Hispanic-majority census tracts had fewer rooftop solar photovoltaics installed compared with those areas with no majority ethnic group, by 69 and 30 percent, respectively. White-majority census tracts had installed 21 percent more.
When correcting for home ownership, black- and Hispanic-majority census tracts had fewer rooftop photovoltaics installed by 61 and 45 percent, respectively, compared with no-majority tracts, while white-majority census tracts had installed 37 percent more.
“The Green New Deal and other environmental justice efforts can use our findings to build a better and more inclusive energy transition,” said Kammen, who is also a fellow of the Berkeley Institute for Data Science and is a former Science Envoy for the U.S. State Department.
“Advances in remote sensing and in ‘big data’ science mean that we are now able to take a unique look at not just where solar is deployed, but to combine that with census and demographic data to chart also who gets to benefit from the solar energy revolution, and therefore think deeper about the effectiveness of current policies and approaches to accelerate solar photovoltaic deployment,” said Sergio Castellanos, a postdoctoral scholar in the Energy and Resources Group and research faculty in the Center for Energy and the Environment. The lead author for the paper is Deborah Sunter, former RAEL postdoctoral fellow and now Assistant Professor of Mechanical Engineering at Tufts University.
The findings were published Jan. 10 in the journal Nature Sustainability. Kammen’s Renewable and Appropriate Energy Laboratory is on the web at rael.berkeley.edu, where the data for the study can be found.
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February 11, 2019: For coverage in The Atlantic & The Pacific Standard, click here.
January 28: For coverage in Forbes, click here.
January 14: For coverage in Greentechmedia, click here.
January 11: For coverage in Sciencedaily, click here.
January 11: For coverage in Solar Power World, click here.
January 10: For the College of Natural Resources story, click here.
Figure: Grid Alternatives solar installation in Bayview-Hunter's Point, with Senator Kevin de Leon and Daniel Kammen
Distributed photovoltaics (PV) have played a critical role in the deployment of solar energy, currently making up roughly half of the global PV installed capacity. However, there remains significant unused economically beneficial potential. Estimates of the total technical potential for rooftop PV systems in the United States calculate a generation comparable to approximately 40% of the 2016 total national electric-sector sales. To best take advantage of the rooftop PV potential, effective analytic tools that support deployment strategies and aggressive local, state, and national policies to reduce the soft cost of solar energy are vital. A key step is the low-cost automation of data analysis and business case presentation for structure-integrated solar energy. In this paper, the scalability and resolution of various methods to assess the urban rooftop PV potential are compared, concluding with suggestions for future work in bridging methodologies to better assist policy makers.
The need to mitigate climate change, safeguard energy security, and increase the sustainability of human activities is prompting a rapid and global transition from carbon-intensive fuels to renewable energy (IPCC 2014). Among renewable energy systems, solar energy has one of the greatest climate change mitigation potentials with life cycle emissions as low as 14 g CO2-eq KWh-1 (carbon dioxide equivalent per kilowatt hour; compare this to 608 g CO2-eq KWh-1 for natural gas). Solar energy embodies diverse technologies able to capture the sun’s thermal energy, such as concentrating solar power (CSP) systems, and photons using photovoltaics (PV). Solar energy systems are highly modular ranging from small-scale deployments (≤ 1 megawatt [MW]; e.g., residential rooftop modules, portable battlefield systems, solar water heaters) to centralized, utility-scale solar energy installations (USSE, ≥1 MW) where a large economy of scale can meet greater energy demands. Nonetheless, the diffuse nature of solar energy necessitates that large swaths of space or land be used to collect and concentrate solar energy into forms usable for human consumption, increasing concern over potential impacts on natural ecosystems, their services, and biodiversity therein. For example, at a capacity factor of 0.20, a single terawatt of USSE capacity scales to 142,857 km2, roughly the area of the state of New York, USA, providing challenges for the integration of potentially massive projects into complex and fragmented landscapes.
The decisions humans make about how much land to use, where, and for what end-use are drivers of Earth system processes. For example, changing the use of land or converting it from one land-cover type to another is a source of greenhouse gas emissions, which are released to the atmosphere when biomass, including soil, is disturbed or removed. How then do we decide when to convert a forest that serves as a carbon sink into a farm that feeds a community, or a farm into a PV park that electrifies a rural village? Innovation and policies directing sustainable pathways of land use for energy and food production can be utilized to address an increasing global population of which 1.5 billion today live without access to electricity. Energy poverty leads to a loss of human health and wellbeing and depressed economic and educational opportunities, particularly for women and children. Our research here is designed to demonstrate, quantify, and facilitate the potential of solar energy systems to address global problems related to climate change, energy access, and the sustainability of food systems, which are interconnected. This research draws from ecological field experiments, knowledge data discovery, geographic information systems, spatial and economic modeling, and is comprised of five interrelated projects:
Environmental co-benefits of solar energy
The Energy-Food-Water Cube: Capability and scalability in on-farm energy production
Global solar energy brightspots: Shinning light on the world’s energy insecure
The land-energy-food nexus in California's Central Valley
Limits of land: Global estimates of land for food and energy
We explore the operations, balancing requirements, and costs of the Western Electricity Coordinating Council power system under a stringent greenhouse gas emission reduction target. We include sensitivities for technology costs and availability, fuel prices and emissions, and demand profile. Meeting an emissions target of 85% below 1990 levels is feasible across a range of assumptions, but the cost of achieving the goal and the technology mix are uncertain. Deployment of solar photovoltaics is the main driver of storage deployment: the diurnal periodicity of solar energy availability results in opportunities for daily arbitrage that storage technologies with several hours of duration are well suited to provide. Wind output exhibits seasonal variations and requires storage with a large energy subcomponent to avoid curtailment. The combination of low-cost solar technology and advanced battery technology can provide substantial savings through 2050, greatly mitigating the cost of climate change mitigation. Policy goals for storage deployment should be based on the function storage will play on the grid and therefore incorporate both the power rating and duration of the storage system. These goals should be set as part of overall portfolio development, as system flexibility needs will vary with the grid mix.
The PACE of clean energy development
The Property Assessed Clean Energy (PACE) program is a national initiative designed to promote investment in solar photovoltaics by commercial, nonprofit, and residential property owners. Its central feature is to provide low-cost, long-term funding, which is repaid as an assessment on the property’s regular tax bill, as is done for sidewalks and sewers, for example. Spurring such investment clearly is a good goal, but is the program effective? Ameli, Pisu, and Kammen in Applied Energy used a natural experiment in northern California to test the capacity of PACE, finding that it has been a great success, more than doubling residential photovoltaic installations in the region at no cost to the taxpayers. —HJS
Appl. Energy 10.1016/j.apenergy.2017.01.037 (2017).
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.
