ArcGIS Living Atlas

Using ArcGIS Living Atlas to locate areas to promote solar

Solar energy is the conversion of sun rays into electricity. It can be done in our households, by installing photovoltaic (PV) panels on our rooftops. In doing so, electricity is being generated where it’s used, decreasing our dependence in an external grid. Solar is a renewable energy source and its use is a sustainable practice, but how can we decide if solar energy can be a reality for our community? Where we are matters a lot. The sun doesn’t shine equally in California and in Belgium. Also, solar panels require a significant initial investment and skilled workers to install them. Let’s explore how Living Atlas of the World can help us identify regions with high solar energy potential and communities that are not currently using solar. 

Best places for solar

The PV electricity output image layer recently released in Living Atlas measures how much electricity (kWh) we can generate per capacity installed (kWp).  For example, in a year we can generate around 2,022 kWh/KWp in Southern California. By contrast, we can only generate about 1,060 kWh/kWp in Belgium.

Solar reliability CA vs Belgium

In addition, a more reliable solar energy value throughout the year is preferable. Solar energy in Southern California is more consistent throughout the year, varying from 4.3 kWh/kWp to 6.2 kWh/kWp per day. In Belgium the differences are larger, in the summer we can produce 4.1 kWh/kWp but only 1.0 kWh/kWp per day in the winter. 

Looking towards the sun 

We can improve the performance of the solar panels by tilting them at the right angle. In doing so, we can generate on average more electricity than with just placing the panels horizontally. The Horizontal and Tilted Irradiations image layer shows the energy that can be generated in a horizontal plane and the energy that can be generated at an optimum tilt angle . For example, in Turin, Italy we can increase the solar energy generated from 1,406 to 1,699 kWh/m2 by tilting the solar panels at the optimal angle of 38°. In contrast, in some other places like in Guayaquil, Ecuador the improvements are marginal (from 1,696 to 1,698 kWh/m2).

Optimal tilt Equator vs Italy

Who is currently using solar and who isn’t? 

Last December, the Living Atlas team updated 78 Living Atlas layers containing American Community Survey (ACS) data within 48 hours of Census releasing the 2014-2018 values. One of the topics we covered was housing tenure by heating fuel type. The boundaries version of this layer will help us identify which tracts have a low percentage of households currently using solar. 

Combining all this information to identify prime areas to promote solar

We now have all the data layers we need straight from ArcGIS Living Atlas. We worked with these layers in both Pro and ArcGIS Online to answer our overall question: Where are good places to promote household solar usage?

Zonal stats

Top 20 untapped areas for solar energy promotion in the US

Implications for policies and incentive programs

Out of the top 20 census tracts that have a high and consistent potential for solar, yet have low current usage rates, 11 of them were in the Victorville/Hesperia area of San Bernardino County, California. Another seven tracts were on the border of Los Angeles and Kern counties, spanning the cities of Lancaster, Mojave, and California City. The top tract is in the Yucca Valley area. These are places that might benefit from some incentive programs that offset or spread out the initial investment.

Areas that already have a relatively high level of solar usage among households, such as Honolulu and San Diego, could serve as blueprints. Evaluation of policies and incentive programs that took place in these areas might help inform the areas above in terms of what works and what doesn’t.

Answering questions using Living Atlas items

We combined three layers from ArcGIS Living Atlas into a simple workflow to identify regions with high solar energy potential and communities that are not currently using solar. We applied certain criteria that made sense for the question we were trying to answer. Working with well-documented and ready-to-use layers such as the PV Electricity Output, Horizontal and Tilted Irradiations, and Housing Tenure by Heating Fuel layers allowed us to get started with our analysis immediately, since lots of the data processing had already been done.

What types of areas will Living Atlas help you identify?

Living Atlas is the foremost collection of maps, apps, and data layers to support your GIS work.  If you have any questions about using ArcGIS Living Atlas, please post them on GeoNetIf you want to go further and use ArcGIS Pro to estimate solar potential, see this Learn LessonYou can find the web map and app we built, along with many other maps that clearly show opportunities to intervene, in Esri Maps for Public Policy.

Thanks to Emily Meriam for cartography assistance!

This blog was updated on 7/1/2020.

About the authors

(she/her/hers) Diana loves working with data. She has 15 years experience as a practitioner of demography, sociology, economics, policy analysis, and GIS. Diana holds a BA in quantitative economics and an MA in applied demography. She is a senior GIS engineer on ArcGIS Living Atlas of the World's Policy Maps team. Diana enjoys strong coffee and clean datasets, usually simultaneously.

Gonzalo Espinoza is a Principal GIS Engineer at ArcGIS Living Atlas of the World. Gonzalo specializes in hydrologic modeling, real time climate and hydro-informatic tools such as flood mapping and forecasting using National Water Model data. He masters the full geospatial tech stack required to develop scalable and operational services relying on large volumes of EO data in the fields of water and environment. At Living Atlas, he also supports the development of workflows for automation of data updates known as Live Feeds, technology used at Esri’s Disaster Response Program. Before ESRI Gonzalo worked in the development of Water Accounting at UNESCO IHE. He holds a PhD in Civil Engineering from the University of Texas at Austin.

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