By Tony G. Reames and Ben Stacey, University of Michigan School for Environment & Sustainability, Urban Energy Justice Lab Michael Zimmerman, University of Michigan College of Literature, Science, and the Arts, Urban Energy Justice Lab
State Energy Efficiency Resource Standards (EERS) have emerged across the United States, becoming prevalent in the early 2000’s. EERS policies are state laws that require utilities to pursue energy efficiency as a cost-effective energy resource. As a result, billions of dollars have been invested in improving residential energy efficiency. The expressed goals of EERS policies include providing consumers direct economic savings by reducing wasted energy, and indirectly through avoided costs of constructing additional power plants. In 2016 alone, twenty-nine EERS states invested $2.5 billion in energy efficiency programs. While utilities regularly surpass annual energy savings goals required by EERS laws, the distribution of program benefits across subpopulations remains a concern for many stakeholders and energy justice advocates. This study takes a novel approach to examining EERS investments through an energy justice lens, taking the first step to assess distributional justice of residential program investments across socioeconomic groups: low-income (or income-qualified) and non-low- income residents. To accomplish this, we develop a comparison metric, known as the Energy Efficiency Equity baseline (E3b), which estimates equitable utility investment proportionate to the low-income population in the service territory and as a percentage of the total residential energy efficiency investment portfolio. This study captures $5.6 billion of spending by eleven Investor-Owned-Utilities (IOUs) from 2012-2021, located in six EERS states: Connecticut, Colorado, Illinois, Massachusetts, Michigan, and Minnesota. The study reveals various distributional disparities in low-income investments and investment trends among utilities, with most underperforming relative to the E3b. However, recent trends suggest improvement by large utilities. Policy revisions, stakeholder intervention, and utility decision-making is beginning to shift this trend.
Each state approaches low-income program requirements differently. The two main factors include:
- Low-income program qualifier: State policy approach es define the population that qualifies for low-income programs,
setting the equity bar for the Energy Efficiency Equity Baseline.
- Minimum spending requirements: States also define (or do not define) the minimum level to be allocated towards
Socioeconomic characteristics (the percent of population qualified for low-income programs) vary greatly across utility territories. The proportion of population eligible for low-income programs varied greatly between 2012-2018 and between utilities, from 23% to 45%. In 2018, the range was 17% to 45%.
The Energy Efficiency Equity baseline (E3b) was developed as a normative baseline metric for utility spending on low-income customers. It effectively accounts for differences in policy approaches, differences in socioeconomic characteristics of each utility territory, and how these factors change overtime. Estimated E3b investments in 2018 ranged from $700,000 to nearly $61 million.
The E3b was used for several performance indicators:
- Annual E3b deficit by year: The largest annual deficit was in 2017 with a shortfall of $91 million. In 2021, the
planned spending levels result in a smaller E3b deficit of $27 million, despite increases in total residential
portfolio spending (low-income plus non-low-income). This reflects substantial shifts in portfolios, emphasizing
low-income programs. This also reflects an overall trend across study states towards more equitable allocations of
residential energy efficiency program spending.
- Cumulative E3b deficit: The cumulative E3b deficit for the eleven IOU’s in this study reached $585 million (2012-
2021), with the largest cumulative deficit for a single IOU at $123 million.
- Rankings: Normalized for portfolio size, E3b performance rankings on an annual basis and lifetime basis can be found
in Table 3.
- E3b performance is likely due to a combination of factors including: state policy parameters (income qualifiers and
spending requirements), as well as utility decision-making. Two notable performances improvements, while associated
with regulatory changes, exceeded low-income spending requirements, moving one utility from #11 to #1, in terms of
annual E3b performance (2015 to 2018).
According to the U.S. Energy Information Administration one in three households experience energy insecurity, or struggle to afford energy, and one in five households are forced to forego other necessities such as food or medicine to pay energy bills.1 In 2016, a study of major U.S. cities found a median annual energy burden (the percent of income a household spends on energy costs) of 3.5%. However, for low-income households the median energy burden was more than twice as high at 7.2%.2 Energy unaffordability varies across the country. One measure that captures the annual dollar gap between affordable energy costs and actual energy costs is the Home Energy Affordability Gap (HEAG). The HEAG, developed by law and economics consulting firm Fisher, Sheehan & Colton, is a function of several factors including: energy prices, housing unit and household size, tenure (owner/renter), heating fuel mix, and local temperature dynamics.3 Figure 1 illustrates the variability of the HEAG for low-income households in six states of interest in this study. The average annual statewide HEAG ranged from $374 in Colorado to $1,847 in Connecticut for households earning at or below 200% of the federal poverty level.