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Improving energy benchmarking with self-reported data

机译：使用自我报告的数据改善能源基准

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摘要

Energy benchmarking for buildings has become increasingly important in government policy and industry practice for energy efficiency. The questions of how energy benchmarking is currently conducted, and how it might be improved using rapidly growing quantities of self-reported data, are examined. A case study of commercial office buildings in New York City demonstrates how the rapid growth in self-reported data presents both new opportunities and challenges for energy benchmarking for buildings. A critique is presented for the scoring methodology and data sources for Energy Star, one of the largest and most successful benchmarking certification schemes. Findings from recent studies are examined to illustrate how this certification currently works in the marketplace. Self-reported building energy data are rapidly growing in Portfolio Manager (the user interface to Energy Star) due to mandatory energy benchmarking laws, and can be used to improve Energy Star's current scoring methods. These self-reported data are tested and improved for analysis by applying theories and methods of data quality developed in computer science, statistics and data management. These new data constitute a critical building block for the development of energy efficiency policies, and will affect how government, consultants, and owners measure and compare building energy use.
机译：在政府政策和行业实践中，为提高能效，建筑物的能源基准测试变得越来越重要。研究了当前如何进行能源基准测试以及如何使用快速增长的自报告数据量来改进能源基准测试的问题。对纽约市商业办公楼的案例研究表明，自报告数据的快速增长如何为建筑物的能源基准测试带来新的机遇和挑战。本文对能源之星的评分方法和数据来源提出了批评，这是规模最大，最成功的基准认证计划之一。对最近研究的发现进行了检查，以说明该认证当前在市场上的运作方式。由于强制性的能源基准测试法，在Portfolio Manager（能源之星的用户界面）中，自报告的建筑能源数据正在迅速增长，可用于改进能源之星当前的评分方法。通过应用计算机科学，统计和数据管理中开发的数据质量理论和方法，对这些自报告的数据进行了测试和改进以进行分析。这些新数据构成了制定节能政策的重要基础，并将影响政府，顾问和业主如何衡量和比较建筑能耗。

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