Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

11-2017

Abstract

This paper discusses the creation of targeting and segmentation information about non-residential buildings that are equipped with advanced metering infrastructure (AMI) meters, or smart meters. Statistics, model, and pattern-based temporal features are extracted from over 36,000 smart meters. They are then merged with a database of past energy efficiency interventions such as lighting, HVAC, and controls retrof its from 1,600 buildings. The buildings are divided into Good, Average, and Poor performing classes according to consumption from before and after the retrofits. Classification models are developed that improve the ability to predict retrofit success and standard industry class by 18.3% and 27.6% respectively over baselines. This study serves as an example of better leveraging smart meter data from non-residential buildings for utility targeted incentive programs. The methodology outlined is preliminary and further models and temporal features are to be tested.

Keywords

Non-residential buildings, Smart meters, Segmentation, Targeting, Retrofit analysis

Discipline

Energy Policy | Environmental Design

Research Areas

Integrative Research Areas

Publication

BuildSys '17: Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments, Delft, Netherlands, November 8 - 9

First Page

1

Last Page

4

Identifier

10.1145/3137133.3137160

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3137133.3137160

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