This blog is the third in a series exploring the findings of IMT’s Putting Data to Work project, a three-year effort to explore how cities and their partners can better deploy building performance data to drive action on energy efficiency in buildings in their jurisdiction. For more information, visit imt.org/PuttingDatatoWork. In this blog, we look at what growing data sets from building energy performance policies may offer utilities.
A growing number of U.S. cities are implementing building energy performance policies that require building owners to report their energy consumption, complete energy audits, or retrocommission their buildings. These policies address issues that are important to cities, such as reducing carbon emissions, increasing accessibility of information about building efficiency, improving net operating income for building owners, and strengthening local real estate markets with high-performance building stock. However, the new treasure trove of data that results—the first-ever energy profile of the cities’ largest buildings—is also of tremendous value to utilities.
When cities implement these policies, they often work with their utilities to ensure that building owners who have to comply with the requirements can get the energy data usage they need without undue burden. IMT’s work in the field is showing us that this isn’t a one-way relationship—not only do many cities want to work proactively and creatively with their utilities to accomplish clean energy goals, but they increasingly have information and tools to offer utilities in the process.
Putting Data to Work, a three-year initiative that examines how benchmarking data is actively used to inform strategic decisions, looked at how cities use the data from building performance policies. As part of this work, IMT identified three big takeaways with real significance for utilities, outlined below.
Cities have data that utilities can use.
Through building performance policies, local governments are collecting new types of data. They’re identifying who owns and manages buildings, and these individuals are often the decision makers on whether to upgrade to more-efficient systems, equipment, and operations. In the case of cities like New York City and Los Angeles, they’re collecting information about building energy systems and equipment that provides insights on how people use energy behind the meter—an area where utilities have traditionally had little insight. In other words, the efforts of cities and utilities can complement each other to create a fuller picture of how to save energy.
New York City, in particular, used its data to identify the prevalence of steam-based energy systems based on energy audit submissions, and worked with Con Edison to revise its rebate offerings to more effectively reach that market. The result is efficiency incentives that are informed by customers’ actual needs. Moreover, audit submissions that include recommended upgrades—like in New York City and San Francisco—may be able to help utilities understand the magnitude of a possible customer base for a particular energy upgrade.
This data can help utilities use their resources more efficiently.
In an era of increasing capital costs and rising consumer expectations, coupled with flattening load, many utilities are learning how to do more with less. Better analytics can be a tool for this. Utilities may be able to work with cities that have implemented building performance policies to reduce their costs associated with customer origination and conversion. In places like New York City and San Francisco, cities are using benchmarking data to proactively reach out to customers and then transfer them to utilities or trade allies when they demonstrate interest in particular energy upgrades, creating a low- or no-cost pipeline of potential customers for efficiency services.
Utilities and cities could take this collaboration further. Utilities and cities could work together to include relevant information on scorecards that cities send to owners about types of efficiency programs that similar buildings have been able to participate in. They could also develop a system so that when a building owner complies with an ordinance, they can opt to send their information to the utility or a utility contractor for efficiency advice.
Moreover, a greater awareness of building energy performance may provide opportunities for utilities to streamline their operations. For example, utilities can deploy targeted energy efficiency and demand response services to owners of low-performing buildings in areas of the distribution grid where load is growing, allowing them to avoid or put off constructing new equipment. While utilities have been testing this approach with success for decades, Con Edison has more recently conducted a pilot that leverages whole-building data.
In the Implementation Guide for Energy Efficiency Program Administrators: Using Building-Level Data to Improve Energy Efficiency, IMT explores ways that program administrators—utilities and their contractors—can use the data from building performance policies as well as how they can actively participate in its creation in collaboration with cities. While there’s still work to be done to quantify the impact of these efforts, early results from interviews with program administrators, utilities, and energy service providers suggest that data from building performance policies can help utilities streamline their operations.
This data is the foundation for innovative new services.
Thinking about energy usage on a building basis could be a game-changer for utilities. While most utilities track customers, meters, or premises, identifying a building can mean learning about the group of customers who share it, how they use energy separately and as a whole, and who is responsible for making decisions about building improvements. The implications of collating that information can be powerful. Data about building energy systems may allow for the development of new efficiency rebates or the validation of pay-for-performance approaches. Utilities could proactively reach out to building owners where whole-building data indicates they may have malfunctioning equipment. Moreover, utilities could consider rate structures or incentives which encourage individual building tenants to work together using energy management systems to produce load profiles that are of value to their area of the distribution grid.
In Emerging Uses for Building Energy Data for Utilities, IMT looks at the next generation of opportunities that utilities can leverage, using building performance policy data to improve their customer service and operations.
In the coming months, furthering the discussion to explore our findings. Specific to utility issues, we’ll be hosting a webinar (whose exact date will be announced in the coming months) that addresses how program administrators can use data more specifically to improve the performance of energy efficiency programs. We’ll also release a more detailed look at the partnership between New York City and Con Edison to improve efficiency offerings.
In the meantime, if you work for a utility or you run efficiency programs and you use this data, we want to hear from you. How do you use it and how do you quantify its impact? If you don’t use it yet, do you want to identify how to get on the path to making use of this data? I welcome your feedback at Kelly.Crandall@imt.org.