Solar Mapping Resources

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Choosing solar energy is a big investment. In order to help consumers quantify the potential benefits, national laboratories and private companies have developed a number of tools to forecast their solar futures. Satellite maps, irradiance data, and real-time bids from installers have been combined to assist customers in understanding the potential costs and benefits of solar with just the click of a button. The examples below help consumers start the process of choosing solar by demonstrating the solar potential of their homes or businesses.


Energy Sage, an Incubator awardee, allows homeowners, businesses, or nonprofit organizations to estimate their energy savings from solar, and connects them with prescreened installers who can provide estimates specific to the user’s address. Users can comparison shop, and select the system that fits their needs best. Electricity bills are used to demonstrate the potential savings from solar energy, and Energy Sage has been found to offer customers substantial savings over more conventional products.


Geostellar measures user’s solar potential based on satellite maps of their property, and will estimate the financial benefit of such a system based on the user’s electricity bills.  Users can compare financial products to determine the payback of a system, see applicable state and federal incentives, and consult with agents to find a system that best meets their needs and wants. Geostellar is an Incubator company.


Mapdwell’s Solar System is an open, online rooftop-solar remote assessment tool that allows any community on earth to discover their underlying solar resources. It reveals the solar potential of building rooftops through state-of-the-art, hyper-precise, advanced technology developed by the Massachusetts Institute of Technology. Communities can use the solar system platform to provide their residents with highly detailed information about the potential of their rooftops or want to better understand their solar resource and increase their solar deployment.

OpenEI Solar Mapping Tools

The OpenEI platform is a wiki, similar to Wikipedia’s Wiki.  Users can view, edit, and add data – and download data for free. OpenEI works to provide the most current information needed to make informed decisions on energy, market investment, and technology development.  On the solar resource page, OpenEI provides maps and links to connect users with solar installers and projects in their neighborhoods.  The platform also connects users to tools like PVWatts and the System Advisory Model, which can be used to estimate solar generation and savings.


PVWatts is an online too from the National Renewable Energy Laboratory that estimates the energy production and cost of energy of grid-connected photovoltaic (PV) energy systems throughout the world. It allows homeowners, business owners, and nonprofit organizations to easily develop estimates of the performance of potential PV installations, based on online map or user supplied data.

San Francisco Energy Map

The San Francisco Energy Map provides an overview of solar and wind energy resources for the city of San Francisco, along with corresponding links and resources, to help residents better understand renewable energy resources and learn how to install their own renewable energy system. The program displays existing solar photovoltaic (PV) and water heating installations in the city. Users can also estimate their rooftop's PV potential, annual system output, associated energy savings, and annual greenhouse gas emissions mitigated. Other links provide cost estimates of installing a solar PV system, ways to find a solar installer, and get more detailed information.

Sun Number

An Incubator awardee, Sun Number gives a numerical score which represents the solar suitability of a building’s rooftop on a scale from 1 to 100, with 100 being the ideal rooftop for solar. Scores can be accessed by entering a valid address in a region where the analysis has been completed. The Sun Number score is created from aerial imagery that is processed with proprietary algorithms to accurately analyze individual rooftops, and based on a combination of factors, each weighted uniquely to provide an accurate analysis of a rooftop. Factors include roof shape, surrounding buildings surrounding vegetation, regional variability, and atmospheric conditions.