Energy benchmarking collects building energy use data sets and measures a building usage against a performance baseline to help building owners and others know how their buildings compare to similar buildings and the impact of energy efficiency (EE) improvements. Fourteen cities, two states (CA and Washington), and one county in the U.S. have passed laws requiring benchmarking for large buildings. U.S. EPA estimates that benchmarking of buildings results in 7% annual savings. However, results from implemented benchmarking initiatives indicate that merely enacting benchmarking laws does not result in savings. Obtaining efficiency savings from benchmarking will require data analytics and visualization tools that can facilitate the translation of data into energy efficiency policy and program recommendations (and tracking the implementation of such recommendations). Currently, few open- source tools exist that allow governments to quickly and accurately translate benchmarking data into recommendations for effective energy efficiency policy and programs.

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This PIE seed project brings together an interdisciplinary Stanford team (EE, policy, data analytics, buildings, behavior) to develop a prototype of an Energy Benchmarking Analytics (EBA) platform, an open-source analytics platform designed to ingest building benchmarking data and translate it into easily understood visualizations tied to energy efficiency policy and program recommendations. Our effort will be structured to work closely with local and state governments who have enacted benchmarking ordinances to identify the tools that will be useful on a practical level, taking into account limited energy expertise and resources.

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Team Member(s): Dr. Zheng Yang, Abigail Andrews

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Collaborator(s): Dian Grueneich (PEEC, Stanford)

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Partner(s): California Energy Comission (CEC)

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Funder(s): Precourt Institute for Energy