April 9, 2019
When it comes to energy, low-income households are stuck between a rock and a hard place. They can’t afford to install energy efficiency measures, so they have more expensive power bills. And higher power bills mean they have less money available to install energy efficiency measures. A new report from NC State researchers aims to shed light on the problem – and inform possible solutions.
The report, “Powering Energy Efficiency and Impacts,” was supported by a grant from the U.S. Department of Energy and involved a broad coalition of partner organizations, including three from NC State: the North Carolina Clean Energy Technology Center, the Center for Geospatial Analytics and the System Design Optimization Lab.
To learn more about the report, how it might influence efforts to help low-income households, and what future directions the research might take, we talked with Anne Tazewell, co-author of the report and special projects manager at the NC Clean Energy Technology Center.
The Abstract: This project evaluates needs, challenges and possible solutions to energy issues facing low-income households. Why is this subject important?
Anne Tazewell: Almost 15% of North Carolina residents live in poverty. That’s close to 1.5 million people. Moreover, the energy needed to heat and cool our homes and prepare our meals is critical to our quality of life. If residents can’t pay their utility bills, these services are turned off. When someone needs to choose between paying their utility bill or insulating their homes – which can reduce their energy use and utility bills – they will choose to pay their bills.
It’s important for there to be more understanding and synergy between energy utilities and agencies whose assistance pays power bills and weatherizes homes. The Powering Energy Efficiency and Impacts Framework project – or PEEIF – brought together a diverse set of partners to focus attention on how big data and mapping can enhance energy-related services to improve the lives of income-challenged households.
TA: What was the scope of this project?
Tazewell: Three entities at NC State University, a regional council of governments, two N.C. nonprofits focused on energy and social justice, a law school and a private sector energy data analytics company created a framework. The project took publicly available data, such as housing square footage from county tax records and the percentage of households living in poverty per census tract, and overlaid it with confidential data to inform and enhance the actions of energy service providers who serve low-income households.
We received data from partner organizations: the N.C. Dept. of Environmental Quality Weatherization Assistance Program and the N.C. Dept. of Health and Human Services Low Income Energy Assistance and Crisis Intervention Programs; Wilson Energy, the electric and natural gas utility serving Wilson, N.C.; Roanoke Electric Cooperative, which serves over 14,000 residents in five northeastern North Carolina counties; and the Town of Enfield electric service utility.
TA: What did you learn?
Tazewell: We learned that this was a unique and ambitious project, and we made some inroads on the challenges that dog many efforts at breaking down the silos that keep mutual interest efforts apart.
For example, in North Carolina, the program managers that oversee federal dollars to increase energy efficiency in low-income households do not have access to the client information for residents who have used federal funds to pay their utility bills. The PEEIF project did not solve this technical and administrative problem, but it got the leadership in both state agencies talking about how to fix it. Furthermore, we now have a legal template for others to use to allow for sharing confidential information that takes into consideration state and federal data security standards and procedures.
We also learned that a picture really is worth a thousand words. Having a map of publicly available data grouped by census tract, such as the population living at or below 150 or 200% of the federal poverty rate, overlaid with confidential information provided by agencies helped inform the potential for county social services and state agencies to see if they have adequately reached all areas of need in their communities.
Further, we demonstrated the potential to combine utility meter data and weather data to calculate energy savings from energy efficiency improvements in homes in our project area that had been weatherized. In other words, we demonstrated a way to better monitor and verify energy savings of specific households that have received assistance. The list goes on. It took us so long to get the legal agreements in place we feel like we had barely scratched the surface of possibilities before the two years of funding from the U.S. Department of Energy ended.
TA: I know that this project focused on a handful of counties in northeastern North Carolina. To what extent might the findings be applied elsewhere?
Tazewell: We partnered with the Upper Coastal Plain Council of Governments, which represents 46 municipalities and five counties in the northeastern part of the state, and what we discovered can be applied anywhere there is a willingness to come together. By aggregating and displaying information from our data providing partners, PEEIF helped encourage more coordination between organizations, and provide a pathway to improve their reach and effectiveness. There are utilities across the country actively engaged in energy efficiency and many also that are faced with customers who are unable to pay their bills. The lost revenue for unpaid bills alone adds up to millions of dollars. Meanwhile there are federal, state and local programs under way everywhere to help increase the effectiveness and efficiency of low-income household energy use.
TA: The report goes beyond reporting findings; it lays out the entire process that you and your collaborators developed for exploring challenges related to energy and low-income households. Is this an approach that could be used elsewhere?
Tazewell: Yes, certainly. The report includes a trove of lessons learned and “how to” steps to help others who want to adopt a similar collaborative approach. There are ways to leverage the overlap in services offered by different entities serving the same population in the same region to make them complementary. In addition, this type of project can help measure the effectiveness of energy efficiency efforts, something that is not practiced in any longitudinal manner in current weatherization programs.
TA: Now that you’ve published the report, are there possible next steps for future work in this area?
Tazewell: We would like to continue with a PEEIF project 2.0 where we could apply some of the lessons learned through our initial two-year effort. It’s a matter of funding. I believe we have a set of data-providing partners that would like to continue, but at this point we are in a holding pattern. Like many innovative projects that have established a proof of concept, we are seeking a new sponsor and/or continued support by a wider community of engaged partners.