Clean Energy for Low Income Communities: Community Assessment and Barriers Analysis

Before launching a new low-income energy program, and even when building upon an existing program, CELICA partners worked to ensure that the planning around such an effort was data-driven. A preliminary low-income community assessment helped several partners identify key issues and provide valuable data to inform development of existing low-income energy programs and support future program planning as well.

Low-income Energy Affordability Data (LEAD) Tool

The LEAD Tool was created with CELICA partners to help state and local stakeholders better understand low-income household energy characteristics. Using data from the US Census, the LEAD Tool allows users to create customizable charts and graphs that compare the type of housing and energy burden of households by income level and housing tenure (i.e., owner vs renter) down to the city and county level. Refer to the LEAD Tool one-pager for a summary. 


Either as part of a community assessment or separately, a barriers analysis helped partners identify gaps in available services and understand underlying conditions that may influence how programs for low-income households operate. A barriers analysis can also help identify additional research needed as part of a planning process and enhance program outreach efforts.

As part of a community assessment and barriers analysis, partners found that engaging with a variety of stakeholders was critical to understanding low-income household needs, goals, and barriers to participation in existing low-income energy programs. The CELICA Stakeholder Engagement section of this toolkit provides information on a range of stakeholders to consider for a community assessment and barriers analysis. 

Elements of community assessment and barriers analysis used by CELICA partners include:

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Low-Income Energy Context

Program design is impacted by a number of external factors, so it is important to understand the overarching energy landscape at the municipal, state, and federal levels. For example, as energy efficiency and renewable programs seek to leverage funding from outside of the energy sector, such as from non-profit or philanthropic organizations, understanding the current landscape is helpful to determine where to go for support. Low-income program design typically requires an understanding of how energy efficiency and renewable resource standards, utility planning cycles, and state climate goals, among other factors, could best be leveraged to support program success.

More detail on the kinds of questions CELICA partners addressed are found below.

As part of researching answers to questions noted below, ask your stakeholders to verify all the information you have is correct. Where CELICA partner examples are available, they are noted below.

  1. What are key energy state or local incentives that currently exist? See the CELICA Case Study: Connecticut's Efforts to Scale Up Integrated Energy Efficiency and Renewables for Low-Income Homes and CELICA Case Study: Colorado's Approach to Low-Income Community Solar Programs that Leverage Weatherization.
  2. What are the factors that enable energy efficiency in low-income communities?
  3. What are the circumstances that enable solar in low-income communities?
  4. What is the infrastructure for other types of services for low-income communities?
  5. What are the utility requirements for low-income programs, carve outs for low-income households, and dedicated public benefit funds (e.g., eligibility requirements, available program funding, and program types)?
  6. How do utility program requirements align with other program requirements and criteria for participation in federal and state weatherization and housing programs, and city funding (e.g., priorities for service, qualifying measure criteria, etc.)?
  7. Are there relevant housing finance agency requirements and incentives (i.e. green building requirements)?
    For example, see the CELICA Promising Practice: Incorporate Energy Efficiency and Renewable Energy Standards as a Criterion in Low-Income Housing Tax Credit Applications
  8. What are the relevant building codes and standards and how do those impact low-income housing (e.g., rental housing)?
  9. Are there programs and incentives that enable solar in low-income communities (e.g. virtual net metering, solar friendly housing utility allowance method for subsidized housing)?
    More detail on the issues and approaches CELICA partners considered are described in the CELICA Issue Brief: Reducing the Energy Burden of Low Income Households in Multifamily Housing with Solar Energy.
  10. Are on-bill tariffs or financing for energy efficiency and renewable energy available in your state?
    For more information on this promising finance mechanism considered by CELICA partners, see the CELICA Issue Brief: Low-income Energy Efficiency Financing through On-Bill Tariff Programs.

It may be useful to break-out answers for each of the above questions by housing sector (single-family, multifamily, manufactured homes) or by housing type (renter or owner occupied) where applicable.

Low-Income Demographics

To help analyze available data on low-income households in order to better understand their low-income communities, CELICA partners worked to answer the questions that follow.

  1. How does energy burden vary across different housing types (e.g., by housing vintage, single-family vs. small and large multifamily, owner occupied vs. renter-occupied) and based on income bracket (i.e., relative to federal poverty level and median income)? And, how does one city or county in your state compare to others across the state, region, or nation?
    Use the LEAD Tool to help identify your local low-income housing and energy use characteristics and communicate those to stakeholders with charts and graphs.
  2. Based on the above data analysis combined with data from other sources (e.g., program data), what are some key insights that you can draw about your low-income community (e.g., where the greatest need is by income, housing type, fuel type and geography)?
  3. How is “low-income” defined in your organization?
    Review the CELICA Issue Brief: Using Data to Set Priorities and Track Success of Low-Income Energy Programs and use the LEAD Tool to understand some of the implications of using different definitions. Many CELICA partners used the income eligibility criteria required by federal, state, and utility programs to align criteria and streamline programs. Others, like the Connecticut Green Bank, used a broader definition based on their goal of reaching all those under the median income.

Use the NREL Solar-for-All Map to view color coded GIS maps of low-income household characteristics, by various income and other demographics. This tool helps users integrate housing affordability and energy burden with health indicators (e.g., data on asthma and infant mortality) and the potential to use energy efficiency and solar power, as well as household resilience indicators (e.g., susceptibility to extreme weather events). Note: the map tool incorporates US Census data found in the LEAD tool.

Low-income Energy Program Funding

The type and level of funding of a low-income energy program will impact all aspects of program design. Certain state and federal funding streams mandate priority populations, have specific eligibility criteria, and dictate how success can be measured and reported. CELICA partners weaved multiple funding streams together for a project to satisfy project funding needs. For example, where one source of funding may not allow funds to be used to repair an aging roof for solar, another funding source might.

DOE worked with CELICA partners to ensure programs fully utilize available federal grant and loan resources. The Low-income Energy Library provides a comprehensive list of federal resources across more than half a dozen federal agencies that may be relevant for low-income energy programs. Information from it can be used to create your own customized Low-Income Energy Program Funding Catalog. This template was based on examples from the states of Tennessee and New York, both of which were CELICA partners.

In addition to taking stock of available federal, state, and utility funds for your low-income energy program, CELICA partners also worked to answer questions such as the ones found below.

  1. What changes are on the horizon in terms of energy landscape, technology, or programs?
  2. What existing funding is available to remediate home, health, and safety issues?
  3. Is financing for energy efficiency currently available for your low-income community?
  4. In which sectors (e.g., multifamily, single-family households with ability to pay, etc.) could financing support energy efficiency and renewable energy in low-income communities?
  5. Who are the main lenders (e.g., community development financial institutions) that lend to affordable housing in the area, and is there any opportunity to work with them as part of an energy program? 

Low-income Community Barriers Analysis

Identify barriers that have historically stood in the way of low-income households accessing energy efficiency and renewable energy programs. These issues may continue to impede access without new approaches as described in the California Low-Income Barriers Study and the CELICA Issue Brief: Using Data to Set Priorities and Track Success of Low-Income Energy Programs.

Additional information about how to identify barriers to low-income household participation in energy programs is described below.

Based on CELICA partners’ experience, what follows are example questions state and local program administrators can consider when conducting analysis of the barriers to low-income household participation in existing energy efficiency and renewable energy programs:


Equitable Access for Different Low-Income Populations

  1. Do programs reach those most in need (those with health conditions, frequent utility shutoffs, young children, etc.)?
  2. Do programs serve diverse communities (e.g., elderly, disabled and others living on a fixed income, working class low-income families, and those from ethnically and racially diverse communities)?
  3. Are programs accessible across a state or region? Is participation concentrated geographically (urban, suburban, rural)?
    Connecticut assessed the distribution of energy efficiency and renewable energy funds to understand how low-income households are benefitting from utility energy efficiency funding and other sources.
  4. Do programs offer convenient access (e.g., locations frequented for other services) to participation by various low-income communities in different languages and using terms that are important to those communities?


Equitable Access for Those Living in Different Housing Types and Conditions

  1. Do program offerings match the ownership patterns in your community?
    Answering this question can help you target efforts to where there is the greatest need and ability to achieve your goals. For example, the CELICA Case Study: Connecticut's Efforts to Scale Up Integrated Energy Efficiency and Renewables for Low-Income Homes describes how data on low-income housing led the state to focus on creating a new program to serve single family low-income owner-occupied housing. As another example, if most low-income households are renting apartments in multifamily properties, are there programs available to assist owners in making major energy upgrades and supporting residents with energy costs and in-unit improvements?
  2. What percentage of households are unable to receive energy efficiency or renewable energy measures due to health and safety or structural issues, and what are the primary issues preventing such services?
    For example, as noted in the CELICA Issue Brief: Promising Examples of Integrated Energy Efficiency and Health Services for Low-income Households, the State of Washington launched and evaluated a weatherization plus health initiative to identify local capacity needed to address major health and safety barriers to energy efficiency. Age of housing is one potential indicator of such issues, and data on this at the state and local level can be found in the LEAD Tool.