An Energy Consumption Intensity Ranking System for Rapid Energy Efficiency Evaluation of a Cluster of Commercial Buildings

dc.contributor.advisorProfessor Michael Ohadi
dc.contributor.authorAditya Ramnarayan, Andres Sarmiento, Armin Gerami, Michael Ohadi
dc.date.accessioned2024-04-12T16:45:14Z
dc.date.available2024-04-12T16:45:14Z
dc.date.issued2023-06
dc.description.abstractBuildings in the U.S. account for roughly 74% of electricity usage and about 40% of all primary energy use associated with greenhouse gas (GHG) emissions. The Nationally Determined Contribution (NDC) for the U.S., as determined in the Paris Agreement, sets a goal of reducing GHG emissions by ~50% compared to 2005 levels by 2030 while working towards achieving net-zero emissions by 2050. To meet these carbon reduction targets, the U.S. must substantially reduce of energy consumption and improve buildings' energy efficiency. To this end, this study introduces an energy consumption ranking tool that can be used to analyze the energy consumption profile of a cluster of buildings/campuses and provide an efficient tool to measure, monitor, and reduce end-use energy and CO2 emissions. The tool bases its rankings on a standard benchmark or a targeted energy efficiency goal. The tool generates a band of ranking, from the best to the worst energy efficiency performance, which directs the attention of building designers, operators, and government regulation/enforcement agencies to buildings having subpar energy efficiency performance. The proposed methodology is extrapolated to encompass a broad range of energy and CO2 consumption metrics in various building types and climate zones, thus having local, regional, and international applications. Using end-use energy utility data from the relevant database for the selected cluster of buildings and campuses, a total square footage area of ~26 million square feet of buildings and campuses was taken as the sample set for performing virtual audits using the custom-developed software. Using dynamic scatter plots and several ranking metrics, buildings with an underwhelming energy performance are identified for detailed energy audits. Once the outliers are spotted, energy modeling is performed to identify and delineate the root cause for the high energy use pattern for the facility. A breakdown of utilities and their corresponding energy analytics are visualized, thus highlighting the range of energy efficiency improvements and the potential for electrification. For the case example studied, the virtual audits are projected to result in minimum annual energy savings of 1,280,461 MMBtu and a corresponding minimum annual GHG reduction of 91,309 metric tons of CO2.
dc.identifierhttps://doi.org/10.13016/y5as-av7a
dc.identifier.urihttp://hdl.handle.net/1903/32420
dc.publisherASHRAE Transactions
dc.relation.isAvailableAtA. James Clark School of Engineeringen_us
dc.relation.isAvailableAtMechanical Engineeringen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us
dc.relation.ispartofseries129 (2)
dc.subjectGHG emissions, energy benchmarking, energy audit, energy efficiency, building energy performance ranking, electrification
dc.titleAn Energy Consumption Intensity Ranking System for Rapid Energy Efficiency Evaluation of a Cluster of Commercial Buildings
dc.typeArticle
local.equitableAccessSubmissionNo

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