Overview

This page provides documentation of the data sources and analytical methods that have been developed to create the Community Solar Opportunity Map.

Key Datasets and Assumptions

Eligible Site Selection

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:

Grid Infrastructure Capacity

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.

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.

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.

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).

Site Nameplate Generation Potential

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 Los Angeles County Solar Map. 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.

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.

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.

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.

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.

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.

Residential Per-Capita Energy Intensity

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.

Solar Electricity Output Offsets

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.

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.

Data Sources

Electricity Consumption Data

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.

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.

Census Block Group Level Statistics

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.

CalEnviroScreen 4.0 (DAC) Census Tracts

Disadvantaged community census tracts (DAC) were downloaded from the OEHHA website. DAC census tracts have scores higher than 75%.

Parcel Zoning Data

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.

Grid Distribution Infrastructure Data

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: DRPEP Layer Metadata.

Building Rooftop Solar Generation Potential Data

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.

Building Footprint Data

Building footprints were generated as a derived dataset from high resolution LiDAR scans performed as part of the LARIAC-5 program.

Parking Lot Footprint Data

Parking lot footprints were generated as a derived dataset from high resolution LiDAR scans performed as part of the LARIAC-5 program.

Solar Generation System Performance

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.

In Front of the Meter Currently Installed Solar Generator Data

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.

Electricity Utility Service Territory Boundaries

Service territory boundaries for Southern California Edison (SCE), the local electricity utility, have been obtained from the California Energy Commission for context.

Community Choice Aggregation Service Territory Boundaries

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.

Brownfield & Superfund Sites

Property locations of US EPA Brownfield and Superfund sites have been downloaded from the US EPA Spatial Data Download Service.

EV Charging Infrastructure

EV Charging infrastructure data has been downloaded from the US DOE AFVD using their public developer API.

Project Team