Applying Advanced Data Analytics to Assess Building Electrification Deployment
Understanding in-field performance is the key to spurring market transformation in home electrification.
Space and water heating account for about 30% of the total emissions in the Northeast. Achieving energy and climate priorities in the Northeast-and across the U.S.- requires utilities and energy agencies to transform the way the built environment is heated and cooled, transitioning buildings away from fossil fuel combustion and to renewably powered heat pumps. To facilitate this transition, policymakers require detailed datasets assessing whole home heat pump performance, that is heat pumps serving 90% or more of home heating load, to inform program design-an analysis that is especially important as states deploy the billions of dollars in IRA funding to spur market transformation in home electrification.
Today, most building thermal loads are served by fossil fuels, including oil, gas, or propane. While the use of cold climate electric heat pumps for both space and water heating has increased over the last decade, the technology has primarily been used for supplemental heating loads (e.g., serving 60% or less of the heating load). Decarbonization of the buildings will require massive deployment of whole home heat pumps, defined as heat pump systems that serve 90% or more of the heating load; however, policymakers have lacked robust datasets on actual, in-field performance and customer satisfaction of whole home heat pumps, resulting in uncertainty about technology performance.
To address these concerns-and drive forward action on building decarbonization-Christie Amero and her team took a deep dive into the performance of whole home heat pump systems, assessing customer satisfaction, utilization, and metered, in-field performance during a typical Northeast winter.
Amero selected over 40 homes across Massachusetts and New York that use their heat pump systems as the primary heating source for in-field metered data collection. In contrast to typical evaluation studies, she focused not only on energy consumption and peak demand, but also assessed what the actual average heating performance was for these systems during a typical heating season and if any backup heating systems were used at these homes. To measure delivered heating load and estimate performance, Amero and her team installed interior supply and return temperature sensors and recorded the indoor heat pump fan power. Then, in combination with the total system demand that was measured at the outdoor unit, she was able to estimate the actual heating performance of the system.
Amero recorded data for each of these points at two-minute intervals for three to seven months, depending on the site. This resulted in millions of data points that her team analyzed in Cadmus’ SQL- based data warehouse. Here she used the data warehouse to stores and analyzes the data, all in one place. She was then able to create an interactive dashboard using Power BI (Business Intelligence) to visualize the results and summarize key objectives (see Figures X and Y). The dashboard gives project stakeholders the opportunity to interact directly with the data. Christie explained her excitement for the Power BI dashboard, “Being able to visualize huge amounts of data in Power BI is exciting and brings out my inner nerd because I love being able to manipulate and work with the data to pull out trends. Our clients loved the accessibility and ease of data visualization.” Working with a compiled dataset for multiple homes and systems allowed our team to extract heating and cooling load, performance, and electric demand impact conclusions over a range of parameters, including outdoor air temperature, home weatherization level, system type, and capacity.
When asked about what is next for heat pump data collection, Christie responded, “I would like to expand this project across the Northeast and the country to collect broader datasets in multiple climate zones and be able to provide statistically significant results. This data will be critical to inform next generation policy and program design, especially as states and the federal government invest billions of dollars in home electrification.”
