Hubbry Logo
Project SunroofProject SunroofMain
Open search
Project Sunroof
Community hub
Project Sunroof
logo
7 pages, 0 posts
0 subscribers
Be the first to start a discussion here.
Be the first to start a discussion here.
Project Sunroof
Project Sunroof
Project Sunroof
View on Wikipedia
from Wikipedia

Project Sunroof is a solar power initiative started by Google engineer Carl Elkin.[2] The initiative's stated purpose is "mapping the planet's solar potential, one roof at a time."[1]

Key Information

Method

[edit]

Project Sunroof primarily works to encourage the private adoption of solar energy by providing a set of tools to facilitate the purchase and installation of solar panels. Using high-resolution 3D imagery data from Google Maps to calculate shadows from nearby structures and trees and taking into account historical weather and temperature patterns, the Project Sunroof website calculates how much money a user can expect to save yearly by making use of solar power.[1] In addition, the Project Sunroof website also provides a list of local solar power retailers capable of installing solar panels in that area.[2]

History

[edit]

Project Sunroof was created by Google engineer Carl Elkin as a 20% time project. While initially launching only in the cities of Boston, San Francisco, and Fresno,[3] the project now displays solar potential for 43 million homes in the US.[4] Google has previously invested in projects with solar energy provider, SolarCity.[5]

While the solar insights provided by Project Sunroof were initially used to support individual rooftop solar insights, additional uses for the data have been developed by Google.

On the Project Sunroof website, Google launched the 'Data Explorer' to allow users to view aggregated solar insights, such as the total number of buildings viable for rooftop solar, or the aggregated solar potential (expressed in megawatts) for entire communities or cities.

In September 2018, Google launched the Environmental Insights Explorer platform.[6] This tool was designed to make it easier for cities to measure their carbon footprint and take action in support of their climate goals. The tool provides estimates for a city's annual carbon emissions using detailed geospatial data derived from Google Maps. It provides an estimate of emissions from the sectors of Transportation and Buildings, and using Project Sunroof data, can also estimate the aggregated solar potential of an entire city to demonstrate the potential to offset emissions using solar energy.

References

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Project Sunroof

View on Grokipedia
from Grokipedia
Project Sunroof is a web-based solar assessment tool created by to evaluate the photovoltaic potential of residential rooftops and estimate associated energy savings and payback periods. The platform processes high-resolution , 3D topographic models, historical weather patterns, and local electricity rates through to determine viable roof surface area, accounting for shading from trees and buildings, optimal panel orientation, and projected annual electricity output. Initiated in August 2015 with coverage in select U.S. regions such as , Fresno, and the , it expanded to all 50 states by early 2017, enabling analyses for over 200 million American homes. By integrating these data-driven insights, Project Sunroof facilitates user connections to certified installers and underscores the scalability of distributed solar generation, revealing that U.S. rooftops possess sufficient capacity to produce terawatts of clean electricity annually under optimal deployment.

Overview

Description and Purpose

Project Sunroof is a free online calculator developed by that assesses the solar potential of residential rooftops by analyzing , rooftop dimensions, and local weather patterns to estimate annual electricity generation, potential cost savings, and payback periods for installations. The tool generates these projections for specific addresses entered by users, highlighting viable solar opportunities based on empirical data such as exposure and suitability, while serving a promotional function by linking users to certified installers for further quotes. Its core purpose is to broaden access to solar feasibility assessments, enabling homeowners to evaluate and financial returns without on-site inspections or specialized expertise, thereby accelerating solar adoption through data-driven insights into geographic and structural variables like and orientation. By aggregating anonymized rooftop data into public explorers for communities and policymakers, Project Sunroof also supports broader planning for distributed solar capacity, emphasizing technical potential over customized engineering. The estimates incorporate average assumptions for efficiency (typically 15-20%), installation costs (around $3-4 per watt), and regional incentives like tax credits, which may vary and thus position the tool as an informational starting point rather than a definitive financial quote. This approach prioritizes scalability and user empowerment, though outputs depend on the accuracy of underlying imagery and generalized inputs, underscoring its role in initial screening rather than final decisions.

Scope and Coverage

Project Sunroof's analysis is limited to residential rooftops within the , evaluating solar potential for approximately 60 million buildings across portions of all 50 states and . The tool generates estimates based on 3D models of roof dimensions, orientation, and shading from trees or nearby structures, derived from aerial imagery and satellite data.. Coverage expanded progressively, starting from select in a handful of states in 2015 to nationwide portions by March 2017.. While the project encompasses data for over half of U.S. households in covered areas, it excludes non-residential structures such as commercial or industrial buildings, focusing exclusively on single-family homes and similar residential properties suitable for individual solar installations.. International applicability remains minimal, with primary operations confined to the U.S. and only limited pilots or availability reported in , lacking broader global deployment.. Coverage gaps persist in rural regions, areas with obstructed or low-quality imagery, and locations where updated aerial data is unavailable, potentially underrepresenting solar potential in less densely populated or topographically complex terrains.. The tool does not account for hyper-local microclimates, variations beyond historical averages, or prospective changes in policy incentives, restricting its functional scope to static, U.S.-residential assessments..

Methodology

Data Sources and Inputs

Project Sunroof relies on high-resolution aerial imagery sourced from and to construct 3D models of buildings and surrounding environments. These models facilitate roof detection and segmentation using algorithms trained on millions of rooftop images, enabling precise delineation of usable roof surfaces while distinguishing them from non-roof elements such as trees. The 3D models derived from this imagery provide key geometric inputs, including roof area, tilt , and (orientation relative to ), which inform potential placement. Shading effects from nearby buildings, trees, and are estimated by simulating paths across all positions, accounting for seasonal variations in solar position. Solar resource data incorporates historical direct normal (DNI), diffuse horizontal (DHI), and temperature values drawn from a commercially available database gridded at 10 km resolution, interpolated where necessary for finer locations. This insolation data reflects long-term patterns rather than short-term forecasts. Supplementary inputs include publicly available datasets on local rates, drawn from and regulatory sources, as well as details on financial incentives such as state and local rebates alongside the federal Investment Tax Credit (ITC). Standard assumptions for photovoltaic panel efficiencies, typically 15-20% for conventional modules, are applied uniformly based on industry benchmarks at the time of model development.

Estimation Algorithms and Processes

Project Sunroof processes inputs such as aerial imagery-derived 3D roof models, local patterns, and geographic through a series of algorithmic steps to estimate production and financial savings. The core estimation begins with techniques applied to high-resolution imagery for roof segmentation, dividing surfaces into directional categories—north, east, south, west, and flat—based on orientation, tilt, and viable area for panel placement. This segmentation informs the calculation of effective roof area, excluding unsuitable portions like chimneys or skylights, while prioritizing south-facing segments in the for maximal insolation. Shading losses are quantified using the 3D models to simulate solar paths across multiple sun positions throughout the year, estimating hourly exposure per square meter and subtracting obstructions from nearby structures or trees. Potential annual energy production is then derived by multiplying this adjusted insolation by the segmented roof area and standard photovoltaic panel efficiency factors, typically incorporating system losses such as inverter efficiency and wiring degradation. The model assumes an annual power degradation rate of 0.5%, reflecting gradual panel output decline over a 20-25 year system lifespan. Economic outputs integrate these physical estimates with location-specific variables, including local rates, policies, solar installation costs, and incentives like tax credits. Savings are computed as the of displaced costs over the system lifetime, factoring in upfront financing options, assumed constant rates for prices, and payback periods derived from total production minus operational expenses. Google's discloses approximate error margins of ±10-20% for production estimates due to variables like unmodeled micro-shading or variability, though the algorithms lack independent peer-reviewed validation beyond internal testing. This approach grounds outputs in basic radiative physics—insolation flux times absorptive area minus losses—but relies on aggregated assumptions that may not capture site-specific anomalies without ground-truth verification.

History and Development

Inception and Initial Launch

Project Sunroof was initiated in 2015 by Carl Elkin, a engineer based in , as part of the company's 20% time policy allowing employees to pursue independent projects. Elkin's motivation stemmed from his personal involvement in local solar advocacy efforts, including volunteering with Solarize Massachusetts, a community group-buy program aimed at reducing solar installation costs through collective purchasing. This hands-on experience highlighted practical barriers to adoption, such as the lack of accessible data on individual rooftop viability, prompting him to repurpose satellite imagery and mapping resources for targeted solar potential analysis rather than broader corporate initiatives. The project's early objectives centered on using high-resolution aerial imagery from , combined with public weather and geographic data, to generate user-specific estimates of solar energy savings and payback periods, thereby addressing informational asymmetries that deterred homeowners from evaluating photovoltaic systems. Initial development emphasized empirical rooftop assessments over speculative promotion, with Elkin leading a small team to prototype the tool without reliance on new data collection. Coverage began narrowly to validate outputs in diverse climates, starting with beta availability in select U.S. metropolitan areas informed by Elkin's regional familiarity. On August 17, 2015, Project Sunroof launched publicly via sunroof.google.com, debuting in three initial cities: Boston, Massachusetts; the , California; and . This rollout provided immediate access for approximately 20 million buildings in these regions, enabling users to input addresses for customized reports on annual sunlight exposure, estimated panel requirements, and 20-year cost savings. The launch prioritized factual, location-based insights to facilitate informed decision-making, with early feedback loops intended to refine estimates before wider expansion.

Expansion and Subsequent Updates

In 2016, introduced the Project Sunroof Data Explorer tool on November 3, enabling users to visualize aggregate solar potential across U.S. zip codes, cities, counties, and states, which facilitated community-level analysis beyond individual rooftops. By March 2017, coverage expanded to all 50 U.S. states, incorporating data for approximately 60 million buildings and integrating existing solar installation maps to highlight regional adoption patterns. In June 2017, a neighborhood view feature was added, displaying red dots for homes with confirmed solar panels to provide comparative context on local installations, leveraging to detect panels from aerial imagery. On May 9, 2018, Project Sunroof updated its , increasing building coverage to 65 million while refining energy production estimates through algorithmic adjustments for factors like and roof orientation, and incorporating current federal, state, and incentives into savings calculations. These refinements depended on accurate data, which fluctuated with policy changes such as tax credits, underscoring the tool's sensitivity to availability for realistic payback projections. In the 2020s, enhancements focused on tracking and third-party accessibility, with post-2022 updates reflecting the Reduction Act's expanded solar credits in savings estimates. The Solar API, launched August 28, 2023, extended Project Sunroof's underlying models for developer use, providing rooftop solar data—including and production estimates—for integration into external tools, though primary operations remained U.S.-centric despite global solar demand. From 2023 to 2025, incremental entries emphasized model tweaks via improved aerial imagery analysis and ongoing synchronization, without structural overhauls to core coverage.

Features and User Tools

Interface and Accessibility

Project Sunroof operates as a web-based application hosted at sunroof.withgoogle.com, allowing users to enter a specific address, , , or broader geographic area to receive tailored evaluations of rooftop solar viability. Upon input, the interface generates interactive outputs such as 3D roof visualizations, color-coded heatmaps indicating sunlight exposure across roof sections, and numerical projections of production in kilowatt-hours annually. The emphasizes simplicity and immediacy, with no mandatory or account creation, facilitating broad access for preliminary self-assessments of solar adoption feasibility. Integrated tools include calculators for estimating installation costs, bill reductions, and payback timelines, assuming conventional system configurations sized between approximately 3 and 10 kW depending on roof capacity and local incentives. These features enable users to explore financing options and long-term without external software or expertise. Complementing the core estimator, the platform incorporates educational components, including explanatory pages on mechanics, installation overviews, and frequently asked questions, to equip users with baseline understanding of photovoltaic systems and related . The interface supports exploration at individual property or aggregate community levels via a data explorer, promoting empirical evaluation of solar potential across neighborhoods or regions. Primarily oriented toward desktop and mobile web browsers, it prioritizes responsive design for cross-device usability, though specialized mobile apps are not provided.

Integrations with Installers and APIs

Project Sunroof enables users to connect directly with local solar installers following the generation of personalized rooftop estimates, facilitating requests for detailed quotes tailored to the site's potential. This integration streamlines the process from to by presenting options from multiple providers in the user's geographic area, allowing comparison of financing, system designs, and installation timelines. Google's Solar API, built upon the computational framework originally developed for Project Sunroof, extends these capabilities to third-party developers and solar enterprises. Launched in 2023 as part of the Platform, the API delivers granular data on rooftop geometry, shading patterns, panel placement configurations, and projected energy yields for over 320 million buildings across 40 countries. Solar companies integrate this API to embed interactive solar assessments within their customer-facing applications, enabling remote pre-designs that minimize on-site evaluations and expedite quoting. Such access supports aggregated data queries for and , permitting firms to identify high-potential regions without individual address disclosures, though usage incurs standard billing based on query volume rather than sales outcomes. Partnerships with utilities and solar marketplaces, including integrations akin to those with EnergySage for verified lead routing, further amplify connectivity, directing users toward pre-qualified installers while forgoes direct transaction fees. This model prioritizes data-driven matchmaking over revenue-sharing, potentially mitigating overt commercial favoritism, though reliance on API-adopting partners may implicitly advantage tech-enabled providers with resources for integration.

Accuracy and Limitations

Validation and Empirical Assessments

Google's internal assessments, derived from analysis of over 100 million U.S. rooftops using aerial imagery and , indicate that approximately 80% are technically suitable for installations based on factors like sunlight exposure, roof orientation, and . These estimates incorporate National Renewable Energy Laboratory (NREL) data for and weather patterns to project annual electricity production. External validations remain limited, with few peer-reviewed studies directly benchmarking Project Sunroof against field-measured outcomes. NREL has independently verified the accuracy of shading analyses in partnered tools like Sighten, which integrate Project Sunroof data, finding remote shading estimates comparable to on-site surveys for preliminary assessments. Comparisons to alternative models, such as the European PVGIS tool, affirm reasonable sunlight potential predictions but highlight variances in projected savings arising from differences in local utility rates, installation costs, and incentive assumptions not fully captured by automated inputs. Empirical checks using installer-verified from reveal that while and production forecasts serve effectively as screening tools, they can overestimate net savings by 10-20% in regions with variable rebate structures or unmodeled site-specific factors like roof degradation or micro-shading. Overall, the tool's outputs align closely with NREL-derived benchmarks for within broad national averages but require on-site validation for precise economic viability, as algorithmic simplifications in cost modeling introduce regional discrepancies.

Criticisms of Estimates and Assumptions

Critics have argued that Project Sunroof's estimates of solar savings are often overoptimistic by underestimating key long-term costs such as panel degradation, inverter replacements, and increased premiums. Solar panels typically degrade at rates of 0.5% to 0.8% annually, leading to output reductions of 10-16% over 20 years, yet the tool's methodology assumes a fixed system life without explicitly adjusting savings for this gradual decline beyond initial projections. Inverter lifespans average 10-15 years, necessitating replacements that can cost 1,000−1,000-3,000, expenses not itemized in Sunroof's default calculations. Homeowners' reports from installer consultations frequently reveal actual periods extending 2-5 years beyond Sunroof's estimates due to unmodeled factors like variations or suboptimal panel orientations missed in satellite-based assessments. The tool's reliance on subsidized incentives, particularly the 30% federal Investment Tax (ITC), inflates projected net savings without fully disclosing dependencies on government policy or taxpayer-funded transfers. Sunroof incorporates current ITC values into cost offsets, yielding savings figures that assume perpetual availability, but legislative proposals as of 2025, including the "One Big Beautiful Bill Act," signal a potential phase-out reducing the credit to 0% for installations post-2025, which could double effective upfront costs for new systems. This approach overlooks the externality of subsidy burdens, where federal credits effectively redistribute costs from solar adopters to non-adopters via tax revenues, distorting economic viability assessments. Project Sunroof neglects intermittency-related system costs, such as the need for grid upgrades or to manage solar's variable output, which can add 20-50% to overall integration expenses in high-penetration scenarios. The focuses on rooftop potential without modeling dispatchable reserves or storage requirements, understating true societal costs where peakers remain essential for reliability during non-sunny periods. Broader critiques highlight omissions in lifecycle analyses, including high upfront emissions from panel manufacturing—often 2,000-4,000 kg CO2-equivalent per kW, primarily from energy-intensive processes in coal-dependent regions—before offsets occur over 1-4 years of operation. Compared to more granular tools like Europe's PVGIS, which incorporates higher-resolution meteorological data and customizable degradation inputs, Sunroof's U.S.-centric modeling yields less precise estimates for edge cases, prioritizing over comprehensive causal factors like local grid constraints.

Impact and Reception

Usage Metrics and Adoption Rates

Project Sunroof has provided solar potential analyses for over 60 million buildings across all 50 U.S. states since its 2015 launch, with full national coverage achieved by March 2017. The tool's data explorer aggregates user queries to reveal regional potentials, such as capacity for hundreds of thousands of existing installations in high-viability areas like , where 312,000 solar systems were identified as of recent data coverage spanning 92% of viable buildings. Adoption metrics include partnerships with more than 40 solar installers nationwide, enabling direct referrals from user estimates to installation quotes. The associated Solar API, launched to extend accessibility, supplies detailed rooftop data for over 320 million buildings, supporting installer and developer integrations that have driven incremental growth in project leads. Engagement concentrates in sunbelt states with superior insolation, where viability exceeds 90% for analyzed rooftops in locations including , , , , , and . These regions show higher query volumes and existing installation densities per the tool's datasets, reflecting both environmental suitability and policy incentives favoring solar deployment. The Framework Convention on awarded Project Sunroof recognition in its Momentum for Change initiative, citing its role in accelerating solar uptake across 42 states as of the evaluation period, with ongoing expansions enhancing national momentum. Despite broad reach, actual conversion from tool-generated leads to completed installations aligns with industry norms for digital solar inquiries, remaining in the low single digits based on installer-reported efficiencies, though precise Sunroof-attributable figures are not publicly disclosed.

Economic and Policy Influences

Project Sunroof has supported economic activity in the solar installation sector by providing homeowners with lists of vetted local providers, thereby generating qualified leads that enable installers to scale operations and secure financing independently of direct intervention. This private-market facilitation has contributed to job growth in solar-related roles, such as installation and , particularly in regions with high estimated rooftop potential, without imposing mandates on adoption. The tool's publicly downloadable datasets have informed analyses, allowing researchers to evaluate spatially targeted for residential solar, as seen in studies proposing designs that account for local generation potential to minimize misallocation under existing federal and state programs. For instance, analyses incorporating Sunroof data have estimated discount rates for solar adoption varying by household wealth, highlighting how influence uptake but often favor higher-income areas. Policymakers have drawn on such insights to refine renewable portfolio standards and credits, though the tool's estimates embed assumptions about stable rates and incentive persistence that may not hold amid market volatility. Critics argue that by factoring in subsidies and current pricing into ROI projections, Project Sunroof can inadvertently promote overoptimistic assessments of solar economics, potentially encouraging installations with extended periods exceeding 15-17 years in unsubsidized scenarios. This risks amplifying interventionist policies that distort private investment decisions, as subsidies—while boosting short-term adoption—fail to address inherent limitations like , which necessitate costly storage and grid upgrades for scalable reliability beyond rooftop viability assessments. Empirical evaluations using Sunroof-derived data underscore that without these supports, financial returns diminish significantly for many households, underscoring the tool's role in highlighting viable private opportunities while exposing the fragility of subsidy-dependent growth.

Environmental and Market Realities

Project Sunroof estimates that widespread adoption of rooftop solar could displace generation, potentially reducing CO2 emissions in regions with high solar insolation, such as parts of the , where average lifecycle for photovoltaic systems range from 40 to 50 grams CO2 equivalent per , significantly lower than coal's 820 g CO2eq/kWh or natural gas's 490 g CO2eq/kWh. These projections align with National Renewable Energy Laboratory (NREL) assessments, which indicate that solar PV can offset emissions from marginal grid generation in sunny locales, assuming effective integration into existing infrastructure. However, the tool's focus on rooftop installations overlooks key environmental trade-offs inherent to solar expansion, including the substantial upstream impacts from rare elements, , and metals like silver for panels, as well as , , and for associated batteries, which involve disruption, , and toxic releases during extraction processes. Distributed rooftop systems also exhibit lower land-use efficiency compared to utility-scale solar farms, which achieve and higher capacity factors through optimized siting, while rooftops contend with shading, orientation limitations, and urban constraints that reduce overall output per unit area. Moreover, solar's intermittency—reliant on variable and —necessitates backup from fossil or other sources during low-generation periods, limiting net decarbonization without massive overbuild or storage, which amplifies material demands. Renewable subsidies underpinning tools like Project Sunroof have drawn criticism for distorting markets by crowding out unsubsidized dispatchable low-carbon options such as , which emits under 12 g CO2eq/kWh over its lifecycle and provides baseload reliability without issues; studies show variable renewables can inadvertently increase system-wide emissions by accelerating nuclear retirements in subsidized environments. While praised by proponents for democratizing solar and encouraging emission-aware choices, Project Sunroof has been faulted for embedding assumptions that favor intermittent renewables, aligning with narratives that impose higher costs on consumers through grid upgrades and reliability measures without commensurate decarbonization gains relative to alternatives.

References

  1. https://sunroof.withgoogle.com/
  2. https://sustainability.google/stories/project-sunroof/
  3. https://spectrum.ieee.org/google-introduces-project-sunroof
  4. https://blog.google/products/maps/shedding-light-solar-potential-all-50-us-states/
  5. https://www.businessinsider.com/google-launches-project-sunroof-2015-8
  6. https://newatlas.com/google-project-sunroof-potential/48420/
  7. https://www.google.com/get/sunroof
  8. https://blog.google/outreach-initiatives/sustainability/project-sunroof-mapping-planets-solar/
  9. https://blog.google/products/maps/project-sunroof-new-data-explorer-tool/
  10. https://www.google.com/get/sunroof/assets/cost-savings-methodology.pdf
  11. https://www.energysage.com/solar/google-project-sunroof-overview/
  12. https://sunroof.withgoogle.com/assets/data-explorer-methodology.pdf
  13. https://pvgis.com/en/blog/pvgis-vs-project-sunroof-comparison
  14. https://www.greenbuildingadvisor.com/article/google-expands-solar-project-nationwide
  15. https://www.google.com/get/sunroof/assets/data-explorer-methodology.pdf
  16. https://sunroof.withgoogle.com/how-it-works/
  17. https://www.theatlantic.com/technology/archive/2017/06/googles-new-product-puts-peer-pressure-to-a-sunny-use/529974/
  18. https://www.architectmagazine.com/technology/google-knows-your-roofs-solar-potential_o
  19. https://techcrunch.com/2015/08/17/panel-panel-on-the-roof/
  20. https://www.utilitydive.com/news/google-launches-project-sunroof-a-treasure-map-for-rooftop-solar/404174/
  21. https://blog.google/products/earth/using-machine-learning-help-people-make-smart-decisions-about-solar-energy/
  22. https://sunroof.withgoogle.com/data-explorer/changelog/
  23. https://blog.google/products/maps/google-maps-apis-environment-sustainability/
  24. https://sunroof.withgoogle.com/data-explorer/
  25. https://sunroof.withgoogle.com/building/35.323807268070155/-119.0366075870179/
  26. https://mapsplatform.google.com/resources/blog/powering-future-our-new-solar-api/
  27. https://sunroof.withgoogle.com/process/
  28. https://unfccc.int/climate-action/momentum-for-change/ict-solutions/project-sunroof
  29. https://developers.google.com/maps/documentation/solar/overview
  30. https://sustainability.google/stories/solar-api-helping-partners/
  31. https://cleantechnica.com/2017/03/22/googles-project-sunroof-claims-80-us-roofs-analyzed-suitable-solar-panels/
  32. https://www.osti.gov/biblio/1436853
  33. https://midwestrenew.org/comparing-sunroof/
  34. https://docs.nrel.gov/docs/fy16osti/65298.pdf
  35. https://www.energysage.com/solar/how-does-solar-panel-degradation-impact-savings/
  36. https://floridasolardesigngroup.com/google-project-sunroof-can-you-trust-it
  37. https://www.greenlancer.com/post/solar-tax-credit-ending
  38. https://resources.environment.yale.edu/gillingham/Valuing_Solar_Subsidies.pdf
  39. https://www.forbes.com/sites/uhenergy/2017/01/24/the-cost-of-wind-and-solar-intermittency/
  40. https://docs.nrel.gov/docs/fy13osti/56487.pdf
  41. https://vriconian.wixsite.com/site/single-post/2018/05/31/solar-pv-is-project-sunroof-a-pvgis-contender
  42. https://www.frontiersin.org/journals/sustainable-cities/articles/10.3389/frsc.2021.632109/full
  43. https://www.pv-tech.org/googles-project-sunroof-increases-operation-to-all-50-us-states/
  44. https://sunroof.withgoogle.com/data-explorer/place/ChIJPV4oX_65j4ARVW8IJ6IJUYs/
  45. https://www.renewableenergyworld.com/power-grid/smart-grids/google-will-use-its-vast-data-and-ai-to-help-deploy-solar/
  46. https://electrek.co/2017/03/14/googles-project-sunroof-data-79-of-us-rooftops-analyzed-are-viable-for-solar-is-yours/
  47. https://techcrunch.com/2015/12/11/googles-project-sunroof-now-tells-more-homeowners-how-well-solar-would-work-on-their-roofs/
  48. https://sunroof.withgoogle.com/data-explorer/featured/1/oklahoma-city
  49. https://www.econstor.eu/bitstream/10419/279195/1/cesifo1_wp10446.pdf
  50. https://sunroof.withgoogle.com/data-explorer/place/ChIJqaUj8fBLzEwRZ5UY3sHGz90/
  51. https://www.eesi.org/articles/view/googles-project-sunroof-could-help-unlock-solar-power-in-the-united-states
  52. https://www.sciencedirect.com/science/article/abs/pii/S0301421523001969
  53. https://www.eurosolar.com.au/uncategorized/the-dark-side-of-solar-energy-understanding-real-environmental-impacts/
  54. https://greenly.earth/en-us/blog/industries/the-harmful-effects-of-our-lithium-batteries
  55. https://www.sciencedirect.com/science/article/pii/S2772940024000304
  56. https://www.linkedin.com/pulse/utility-scale-solar-vs-distributed-advantages-part-2-aftab-raza-nyorc
  57. https://pvcase.com/blog/solar-power-pros-and-cons
  58. https://www.sciencedirect.com/science/article/pii/S2589004222000116
  59. https://environmentalprogress.org/big-news/2016/7/14/bloomberg-new-energy-finance-renewables-killing-nuclear
Add your contribution
Related Hubs
User Avatar
No comments yet.