Document Type

Conference Paper

Subject Area

CPS Efficient Buildings, CPS Internet of Things

Date of this Version

9-2015

Publication Source

SRC TECHCON 2015

Comments

Publication ID:P084437

Best Paper Award in the Internet of Things Session

Abstract

Unprecedented amounts of information from millions of smart meters and thermostats installed in recent years has left the door open for better understanding, analyzing and using the insights that data can provide, about the power consumption patterns of a building. The challenge with using data-driven approaches, is to close the loop for near real-time control and decision making in large buildings. Furthermore, providing a technological solution alone is not enough, the solution must also be human centric. We consider the problem of end-user demand response for commercial buildings. Using historical data from the building, we build a family of regression trees based models for predicting the power consumption of the building in real-time. We have built DR-Advisor, a recommender system for the building's facilities manager, which provides optimal control actions to meet the required load curtailment while maintaining building operations and maximizing the economic reward.

Keywords

demand response, machine learning, data, CPS, buildings

Bib Tex

@ARTICLE {behl_TECHCON15, author = "Madhur Behl and Rahul Mangharam", title = "Sometimes, Money Does Grow on Trees: DR-Advisor, A Data Driven Demand Response Recommender System", journal = "SRC TECHCON 2015", year = "2015", number = "P084437", month = "sep", note = "Best Paper Award in the Internet of Things Session" }

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Date Posted: 15 January 2016

This document has been peer reviewed.