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Implementations of Energy Benchmarking Disclosures

Jeffrey Lin

Energy benchmarking refers to both mandated and voluntary provisions adopted by a governmental entity for building owners to report building energy usage to the governmental entity, for which results often are also published by the governmental entity for the general public. Benchmarking programs vary in complexity, but typical implementations require the longitudinal survey of energy metrics, with the ability to compare energy performance relative to comparable buildings. Almost all energy benchmarking programs include components for reporting and disclosure. Extensive energy and building data is reported to the relevant local authority, which minimally includes monthly resource consumption data and self-reported building characteristics. The building is benchmarked against other buildings in its class, and summary data is often but not always publicly disclosed. The information publicly disclosed varies widely, but typically includes energy use intensity (EUI) and a comparison metric or score.

It is often assumed that energy efficiency benchmarking follows a virtuous cycle—data is collected, energy benchmarking is performed, stakeholders act to increase energy efficiency, and measurement and verification is conducted to inform future policies. At a more granular level, how energy efficiency programs translate programs and data into actual efficiency gains is less well-understood.

Massive energy efficiency savings have been attributed to energy benchmarking. For example, an Institute for Market Transformation (IMT) review concluded that buildings which participated in benchmarking reduced energy consumption by 2.4% each year; in Washington, D.C., benchmarked buildings were credited with reducing energy use by 9% over a three-year period.1 In reviewing its building benchmarking program, New York City found that emissions for benchmarked properties decreased by 8 percent over 2010 to 2013, contrary to 2007 predictions of a 27 percent increase over 2007 to 2030 under business-as- usual assumptions. 2 So far, the primary pathway for these reductions has required a proactive building manager and/or owner. Without a benchmarking mandate, few if any building managers or owners know how their energy consumption compares to equivalent buildings. With a mandatory benchmarking process and publicly disclosed benchmark data, the building owner or manager has both the knowledge and impetus to act on identified energy efficiency improvements. However, building benchmarking provides many additional policy opportunities, including allowing for energy efficiency outreach programs, providing research data for academics, industry, and for power systems planning,

Several reports have been produced on the state of benchmarking in various state, county, and local jurisdictions. These include those by IMT, BuildingRating3, Lawrence Berkeley National Lab (LBNL)4, and CBRE. These reports typically cover the requirements and compliance history of each program. Similarly, there have been several reports on the status of transparency and disclosure in energy efficiency programs, including that by the City of Seattle. While there is some overlap between these reports and this thesis, this thesis  focuses on the legal and organizational source of data disclosure, with the aim of understanding why and how data is disclosed. This thesis also identifies best practices for disclosure, so that all stakeholders—energy efficiency program administrators and implementers, building owners and managers, and researchers—can best obtain, submit, and analyze benchmarking data. In doing so, this thesis investigates how different cities have approached energy benchmarking and building data disclosure, with the purpose of informing how future energy efficiency programs could be coordinated with benchmarking efforts.

This thesis is the policy component of the Energy Benchmarking Analytics (EBA) platform project at Stanford University, led by Professor Rishee Jain and Dian Grueneich. The EBA platform uses a stochastic frontier analysis (SFA) method to output a benchmark score which correlates well with both Energy Star Portfolio Manager scores and direct EUI measures. A key advantage of the EBA platform is its ability to ingest many data fields and provide a scoring of each field’s relevance, and the technique works well on data sets which are either sanitized or can be combined cleanly. Disclosure of high-quality building data allows the EBA platform to generate more effective analyses of building characteristics which contribute to energy efficiency. Similar academic5, research, and commercial6 efforts also contribute to our understanding of building energy use and efficiency programs; improved data disclosure is vital for these efforts.