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<title>Methods | LA Community Solar Opportunity Map</title>
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<h1>Methods</h1>
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<aside class="toc">
<h3>Table of Contents</h3>
<ul>
<li><a href="#overview">Overview</a></li>
<li><a href="#keydata">Key Datasets and Assumptions</a></li>
<!-- <ul>
<li><a href="#grid_capacity">Grid Infrastructure Capacity</a></li>
<li><a href="#nameplate_generation">Solar Generation Potential</a></li>
<li><a href="#res_usage_intensity">Residential Energy Intensity</a></li>
<li><a href="#solar_output_offsets">Electricity Output Offsets</a></li>
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<li><a href="#sources">Data Sources</a></li>
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<li><a href="#elec_consumption">Electricity Consumption</a></li>
<li><a href="#census">Census ACS</a></li>
<li><a href="#ces">CalEnviroScreen 4.0</a></li>
<li><a href="#parcels">Parcels Zoning</a></li>
<li><a href="#circuits">Distribution Circuits</a></li>
<li><a href="#rooftop_potential">Rooftop Solar Potentials</a></li>
<li><a href="#building_footprints">Building Footprints</a></li>
<li><a href="#parking_lots">Parking Lot Footprints</a></li>
<li><a href="#system_performance">Solar PV System Performance</a></li>
<li><a href="#ifom_installed">Installed IFOM Solar PV</a></li>
<li><a href="#iou_territory">IOU Service Territory</a></li>
<li><a href="#cca">CCA Service Territory</a></li>
<li><a href="#brownfields">Brownfields & Superfund Sites</a></li>
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<h2 id="overview">Overview</h2>
<p class="lede">
This page provides documentation of the data sources and analytical methods that have been developed to create the Community Solar Opportunity Map.</p>
<h2 id="keydata">Key Datasets and Assumptions</h2>
<h3>Eligible Site Selection</h3>
<p>
The design plan for this tool includes the following criteria which are used for initial identification of “eligible sites” for the development of community scale solar generation or resiliency center assets. The criteria of eligibility are listed below:</p>
<ul>
<li>
Eligible sites should be restricted to institutional, publicly owned, and community-oriented properties with existing buildings. This requirement is meant to ensure that the development of solar PV assets on these sites will be categorically exempt from California Environmental Quality Act (CEQA) review requirements. Sites that could only support ground mounted arrays on previously undeveloped lands were not included.</li>
<li>
Eligible sites possess existing metered electricity accounts. The requirement is meant to ensure that one or more existing accounts are available that could be used to support the solar PV installation. The presence of buildings larger than 400 ft^s in footprint area was used as a proxy for the existence of a metered electricity account.</li>
</ul>
<h3 id="grid_capacity">Grid Infrastructure Capacity</h3>
<p>
Grid infrastructure capacity metrics for each distribution circuit have been developed by the local investor owned utility, Southern California Edison (SCE), as part of an integrated capacity assessment performed in support of their distributed energy resource planning efforts. Within SCE service territory, there are different relevant capacity metrics for distributed energy resource planning depending upon whether the planned system is intended to be interconnected to the distribution grid from in front of or behind the customer's meter.</p>
<p>
For behind the meter (BTM) systems, interconnections are governed by a regulatory framework called Rule-21, which details utility procedures and requirements for the submission of distributed energy resource grid integration requests. Rule-21 provides for a “fast track” interconnection application provided that the total combined nameplate capacity of all generation assets connected to each distribution circuit does not exceed 15% of the historical maximum load experienced on that circuit over the previous ~18 months. This 15% limit is called the 15% penetration capacity and is defined for each named circuit. Projects that exceed the remaining capacity are assigned to a “detailed study” category, making them more expensive, time consuming, and their outcomes more uncertain. </p>
<p>
For systems that are intended to be interconnected to the distribution grid in front of a customer's meter, and participate in the wholesale market for power generation, a different circuit capacity meteric applies. For these types of in front of the meter (IFOM) systems, the maximum allowable PV generation limit for the closest circuit segment is shown for each eligible site. </p>
<p>
As part of this analysis, each eligible site must be associated with its proximal distribution circuit in order to assess the extent to which the full development of that site's available solar PV generation potential will or will not exceed relevant capacity limits. Additionally, for in front of the meter system designs, local residential accounts must also be associated with their proximal circuits in order to determine which accounts can potentially be served by a VNM scheme implemented at any individual candidate site. Because publicly available spatial data layers of grid infrastructure do not show parcel-to-grid connections, these circuit-to-site and circuit-to-account relationships have all been assigned on the basis of minimum geographic distance. This is the same allocation procedure used by (Porse et al. 2020).</p>
<h3 id="nameplate_generation">Site Nameplate Generation Potential</h3>
<p>
Two types of solar PV systems are considered by the tool: rooftop and parking canopy mounted systems. As rooftops are existing structures that can be remotely sensed using aerial/satellite imagery & LiDAR, there are established methods for calculating the potential nameplate size of rooftop mounted PV. These methods account for roof size, orientation, obstacles, and local shading factors. The rooftop solar potentials of all of the buildings within Los Angeles County have already been estimated using these methods as part of the development of the <a href="https://planning.lacounty.gov/solar/" target="_blank">Los Angeles County Solar Map</a>. This data has been leveraged as part of this analysis to provide a comprehensive estimate of the total combined rooftop system potential associated with all of the buildings located on each eligible site. A conservative estimate for each site was generated by using kW solar potential values for only those rooftop areas with the highest ("excellent") suitability grading.</p>
<p>
In addition to rooftop PV system capacities, the availability of detailed information about the geographic extents of parking lots within the region creates the opportunity to assess the solar potential (MW) of canopy mounted systems as well. However, as canopy structures must be fabricated, and thus, do not yet exist, procedures for estimating their potential are not as well-established, nor are similar estimates for LA County buildings readily available.</p>
<p>
Our approach to estimating the solar potential of parking lot canopy structure mounted systems on eligible candidate sites involves a set of assumptions about the fraction of a site’s parking lot area that could potentially be covered by canopy structures. To be conservative about our solar potential estimates, the specific value for this “site density factor” that was used to develop the tool was 15%. This means that only 15% of the total available parking lot surface area is expected to be able to have canopy structures installed.</p>
<p>
This choice of this 15% value is based on an analysis of the ratio of available parking lot areas to installed canopy structure areas for existing generator facilities which have throughout the region as well as a review of the academic literature on the design and performance characteristics of such "carport" solar PV systems.</p>
<p>
Once the canopy structure footprint area estimates have been established, these values can then be multiplied by a corresponding "panel density factor" which represents the total panel area that can be installed on the footprint area of a given canopy structure. Finally, once the total panel area estimates have been established, the output of these panels can be modeled using solar insolation and system performance characteristics for the site's location using the National Renewable Energy Laboratory's PVWatts Model API.</p>
<p>
While these approximation techniques are admittedly coarse, they should be useful in providing an order of magnitude level estimate of the potential for parking lot canopy structures to contribute to a site's total solar PV generation potential. This is increasingly becoming an essential consideration as parking lot canopy structure mounted systems have grown in popularity throughout the region in recent years.</p>
<h3 id="res_usage_intensity">Residential Per-Capita Energy Intensity</h3>
<p>
Annual account level residential electricity consumption data from the UCLA Energy Atlas were aggregated to the Census Block Group level. This value was then divided by the block group's population to estimate average per-capita residential electricity demand.</p>
<h3 id="solar_output_offsets">Solar Electricity Output Offsets</h3>
<p>
Based on shared distribution circuit associations, average residential per-capita electricity consumption values were linked to nearby eligible sites in order to estimate (on a per-capita and per-household basis) how much residential electricity use could be offset by solar PV generation at that site. Estimates for households are broken down by renter and owner households, based on census data. </p>
<p>
Residential households whose electricity could be offset were restricted to those which are connected to the same local distribution circuit as the eligible site in question. This is meant to minimize the potential risks of experiencing reverse power flows along any particular circuit in the event of a temporary imbalance between supply and demand.</p>
<h2 id="sources">Data Sources</h2>
<h3 id="elec_consumption">Electricity Consumption Data</h3>
<ul>
<li><i>Source:</i> UCLA Energy Atlas Back-end Database</li>
<li><i>Access:</i> Private</li>
<li><i>Info:</i> <a href="https://www.energyatlas.ucla.edu" target="_blank">UCLA
Energy Atlas</a></li>
<li><i>Dates:</i> Data year: 2019, Data accessed: June 2020</li>
</ul>
<p>
Energy consumption data used for the development of the solar opportunity tool has been sourced from the UCLA Energy Atlas back-end database. This is the raw source data that is used to develop the aggregated data which is publicly displayed within the UCLA Energy Atlas front-end website. These data have been obtained from the California Public Utilities Commission (CPUC) under a binding non-disclosure agreement.</p>
<p>
This back-end Energy Atlas database contains account level monthly electricity consumption for all metered accounts within Southern California Edison service territory over a period spanning 2006-2019. These account level data records are stored in a secure computing facility on the UCLA campus and are subject to strict cyber-security protocols. Additionally, all research applications of this data comply with CPUC mandated rules for the privacy preserving aggregation of account level consumption records.</p>
<h3 id="census">Census Block Group Level Statistics</h3>
<ul>
<li><i>Source:</i> U.S. Census Bureau American Community Survey</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i> <a
href="https://www.census.gov/programs-surveys/acs/data.html" target="_blank">Census.gov</a>
</li>
<li><i>Dates:</i> Data year: 2019, Data accessed: June 2020</li>
</ul>
<p>
Census block group level statistics from the 2018 vintage of the American Community Survey were downloaded for use in this analysis. Information for total population, renter/owner, and average household size per block group were incorporated into the analysis.
</p>
<h3 id="ces">CalEnviroScreen 4.0 (DAC) Census Tracts</h3>
<ul>
<li><i>Source:</i> Office of Environmental Health Hazard Assessment (OEHHA)</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i> <a
href="https://oehha.ca.gov/calenviroscreen/report/calenviroscreen-30" target="_blank">OEHHA</a>
</li>
<li><i>Dates:</i> Data year: 2021, Data accessed: January 2022</li>
</ul>
<p>
Disadvantaged community census tracts (DAC) were downloaded from the OEHHA website. DAC census tracts have scores higher than 75%.
</p>
<h3 id="parcels">Parcel Zoning Data</h3>
<ul>
<li><i>Source:</i> Los Angeles County Assessor's Office</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i> <a
href=" https://egis-lacounty.hub.arcgis.com/documents/parcels/about" target="_blank">egis-lacounty.hub.arcgis</a>
</li>
<li><i>Dates:</i> Data year: 2022, Data accessed: Jan 2022</li>
</ul>
<p>
Standardized parcel zoning data for the Los Angeles County region were obtained from the Los Angeles County Parcel Assessor for the year 2020. The assessor's parcel database was downloaded from Los Angeles County's Socrata Open Data portal.
</p>
<h3 id="circuits">Grid Distribution Infrastructure Data</h3>
<ul>
<li><i>Source:</i> Southern California Edison Distributed Resource Planning External Portal (DRPEP)</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i> <a href="https://ltmdrpep.sce.com/drpep/" target="_blank">SCE</a>
</li>
<li><i>Dates:</i> Data year: 2022, Data accessed: February 2022, Updated Monthly</li>
</ul>
<p>
In front of the meter (IFOM) and behind the meter (BTM) grid distribution circuit capacity layers were programmatically accessed from the SCE DRPEP web- map application's REST API. Reported IFOM capacities are based upon the Integrated Capacity Assessment layer's "Overall PV" attribute. Reported BTM capacities are based upon the RAM Circuit layer's "15% Penetration Limit" attribute. The attributes associated with these and other layers contained within the SCE DRPEP portal are documented at the following location: <a href="https://services5.arcgis.com/z6hI6KRjKHvhNO0r/ArcGIS/rest/services/ICA_Layer/FeatureServer" target="_blank">DRPEP Layer Metadata</a>.
</p>
<h3 id="rooftop_potential">Building Rooftop Solar Generation Potential Data</h3>
<ul>
<li><i>Source:</i> Los Angeles County Rooftop Solar Map</li>
<li><i>Access:</i> Private</li>
<li><i>Info:</i> <a
href="https://apps.gis.lacounty.gov/solar/m/?viewer=solarmap" target="_blank">LA
County</a></li>
<li><i>Dates:</i> Data year: 2021, Data accessed: January 2022</li>
</ul>
<p>
Building Rooftop solar estimates were generated by the consulting firm Critigen - a sub- contractor to the Environmental Services Firm CH2M-Hill - for the Los Angeles County Internal Services Department as part of the development of the County's Solar Map. These solar estimates were modeled using detailed information about incident solar radiation intensities, micro and mesoscale shading, and building rooftop surface areas and orientations derived from high resolution LiDAR scans performed as part of the LARIAC-5 program. These estimates were then aggregated to the parcel level and reported in terms of total suitable area for the installation of solar panels.
</p>
<h3 id="building_footprints">Building Footprint Data</h3>
<ul>
<li><i>Source:</i> Los Angeles Regional Imagery Acquisition Consortium
(LARIAC-5)</li>
<li><i>Access:</i> Private</li>
<li><i>Info:</i> <a
href="https://lariac-lacounty.hub.arcgis.com/" target="_blank">LARIAC</a></li>
<li><i>Dates:</i>Data year: 2017, Data accessed: March 2019</li>
</ul>
<p>
Building footprints were generated as a derived dataset from high resolution LiDAR scans performed as part of the LARIAC-5 program.
</p>
<h3 id="parking_lots">Parking Lot Footprint Data</h3>
<ul>
<li><i>Source:</i> Los Angeles Regional Imagery Acquisition Consortium
(LARIAC-5)</li>
<li><i>Access:</i> Private</li>
<li><i>Info:</i> <a
href="https://lariac-lacounty.hub.arcgis.com/" target="_blank">LARIAC</a></li>
<li><i>Dates:</i>Data year: 2017, Data accessed: March 2019</li>
</ul>
<p>
Parking lot footprints were generated as a derived dataset from high resolution LiDAR scans performed as part of the LARIAC-5 program.
</p>
<h3 id="system_performance">Solar Generation System Performance</h3>
<ul>
<li><i>Source:</i> National Renewable Energy Laboratory, PVWatts
Calculator V5</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i> <a
href="https://developer.nrel.gov/docs/solar/pvwatts/v5/" target="_blank">NREL</a>
</li>
<li><i>Dates:</i> Data year: June 2020, Data accessed: June 2020</li>
</ul>
<p>
The National Renewable Energy Laboratory has developed a toolset for estimating solar generation facility performance called PV-WATTS. This toolset incorporates geographically specific data about solar insolation intensities as well as up-to-date technical parameters about system component efficiencies. The fifth version of the PV-WATTS toolset is accessible via programmatic API call and can be used to automate the process of estimating the performance characteristics of systems installed on a large number of potential sites.
</p>
<h3 id="ifom_installed">In Front of the Meter Currently Installed Solar Generator Data
</h3>
<ul>
<li><i>Source:</i> California Energy Commission (CEC) Generator
Facility Database</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i> <a
href="https://cecgis-caenergy.opendata.arcgis.com/app/ad8323410d9b47c1b1a9f751d62fe495" target="_blank">CEC</a>
</li>
<li><i>Dates:</i> Data year: 2021, Data accessed: January 2021</li>
</ul>
<p>
The California Energy Commission (CEC) maintains a database of permitted in front of the meter generator facilities. These facilities are generally large utility scale assets which sell power to the grid at wholesale rates. Each facility is coded by fuel type and has listed as an attribute its nameplate generation capacity. The locations of these existing large scale, in-front of the meter (IFOM) solar PV generators within LA County have been cross-referenced with the locations of eligible community scale generation sites to determine the extent to which a site's solar energy potential has already been developed.
</p>
<h3 id="iou_territory">Electricity Utility Service Territory Boundaries</h3>
<ul>
<li><i>Source:</i> California Energy Commission</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i> <a
href="https://www.energy.ca.gov/data-reports/energy-maps-california" target="_blank">CEC</a>
</li>
<li><i>Dates:</i> Data year: 2020, Data accessed: June 2020</li>
</ul>
<p>
Service territory boundaries for Southern California Edison (SCE), the local electricity utility, have been obtained from the California Energy Commission for context.
</p>
<h3 id="cca">Community Choice Aggregation Service Territory Boundaries</h3>
<ul>
<li><i>Source:</i> Clean Power Alliance (CPA)</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i> <a href="https://cleanpoweralliance.org/" target="_blank">CPA</a>
</li>
<li><i>Dates:</i> Data year: 2020, Data accessed: June 2020</li>
</ul>
<p>
Service territory boundaries for the Clean Power Alliance (CPA), the local Community Choice Aggregation (CCA), have been assembled from published material about the organizations member cities and municipalities.
</p>
<h3 id="brownfields">Brownfield & Superfund Sites</h3>
<ul>
<li><i>Source:</i> US EPA Spatial Data Download Service</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i><a href="https://www.epa.gov/frs/geospatial-data-download-service/" target="_blank"> US EPA</a>
</li>
<li><i>Dates:</i> Data year: 2020, Data accessed: November 2020</li>
</ul>
<p>
Property locations of US EPA Brownfield and Superfund sites have been downloaded from the US EPA Spatial Data Download Service.
</p>
<h3 id="ev_charging">EV Charging Infrastructure</h3>
<ul>
<li><i>Source:</i>United States Department of Energy (US DOE)</li>
<li><i>Access:</i> Public</li>
<li><i>Info:</i> <a href="https://afdc.energy.gov/" target="_blank">US DOE Alternative Fuel Vehicle Datacenter (AFVD)</a>
</li>
<li><i>Dates:</i> Data year: 2022, Data accessed: January 2022</li>
</ul>
<p>
EV Charging infrastructure data has been downloaded from the US DOE AFVD using their public developer API.
</p>
<h2 id="team">Project Team</h2>
<ul>
<li><a href="https://www.ioes.ucla.edu/person/eric-fournier/" target="_blank">Eric
Daniel Fournier</a>, Research Director (CCSC)</li>
<li><a href="https://www.ioes.ucla.edu/person/lauren-strug/" target="_blank">Lauren
Strug</a>, Geospatial Analyst/Front-end Developer (CCSC)</li>
<li><a href="https://www.ioes.ucla.edu/person/scott-gruber" target="_blank">Scott
Gruber</a>, Web Developer and UX Designer (IoES)
</li>
<li><a href="https://www.ioes.ucla.edu/person/robert-cudd/" target="_blank">Robert
Cudd</a>, Research Analyst (CCSC)</a></li>
<li><a href="https://www.ioes.ucla.edu/person/hannah-gustafson/" target="_blank">Hannah
Gustafson</a>, Geospatial Analyst/Front-end Developer (CCSC)
</li>
<li><a href="https://www.ioes.ucla.edu/person/felicia-federico/" target="_blank">Felicia
Federico</a>, Project Manager, Executive Director (CCSC) </li>
<li><a
href="https://www.ioes.ucla.edu/person/stephanie-pincetl/" target="_blank">Stephanie
Pincetl</a>, Principal Investigator, Founder & Director (CCSC)
</li>
</ul>
</main>
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<address>
<a href="https://ioes.ucla.edu/ccsc" target="_blank"><b>CALIFORNIA CENTER FOR
SUSTAINABLE COMMUNITIES at
UCLA</b></a><br>
<i><small> Updated: 6/17/2022 </small></i>
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