DOI: 10.1016/j.enpol.2020.111327
论文题名: Examining the feasibility of using open data to benchmark building energy usage in cities: A data science and policy perspective
作者: Roth J. ; Lim B. ; Jain R.K. ; Grueneich D.
刊名: Energy Policy
ISSN: 03014215
出版年: 2020
卷: 139 语种: 英语
中文关键词: Benchmarking
; Building energy performance
; Disclosure policy
; Energy efficiency
; Open data
; Variable selection
英文关键词: Benchmarking
; Decision trees
; Energy efficiency
; Energy utilization
; Office buildings
; Random forests
; Benchmarking models
; Building characteristics
; Building energy performance
; Disclosure policies
; Energy benchmarking
; Supporting policies
; Urban energy consumption
; Variable selection
; Open Data
; benchmarking
; building
; data set
; energy efficiency
; energy policy
; energy use
; feasibility study
; performance assessment
; policy analysis
; urban area
英文摘要: Buildings are by far the largest source of urban energy consumption. In an effort to reduce energy use, cities are mandating that buildings undergo energy benchmarking—the process of measuring building energy performance in order to identify buildings that are inefficient. In this paper, we examine the feasibility of using city-specific, public open data sources in two benchmarking models and compare the results to the same models when using the Commercial Building Energy Consumption Survey (CBECS) dataset, the basis for Energy Star. The two benchmarking models use datasets containing building characteristics and annual energy use from ten major cities. To examine the difference in performance between linear and non-linear models, we use random forest and lasso regression. Results demonstrate that benchmarking models using open data outperform models based solely on the CBECS dataset. Additionally, our results indicate that building area, property type, conditioned area, and water usage are the most important variables for cities to collect. Having demonstrated the benefits of using open data, we recommend two changes to current benchmarking practices: (1) new guidelines that support a data-driven benchmarking framework relying on open data and a transparent modeling process and (2) supporting policies that publicize benchmarking results and incentivize energy savings. © 2020 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/167449
Appears in Collections: 气候变化与战略
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作者单位: Urban Informatics Lab, Department of Civil & Environmental Engineering, Stanford University, United States; Precourt Institute for Energy, Stanford University, United States
Recommended Citation:
Roth J.,Lim B.,Jain R.K.,et al. Examining the feasibility of using open data to benchmark building energy usage in cities: A data science and policy perspective[J]. Energy Policy,2020-01-01,139