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Title: Creating an Energy Intelligent Campus: Data Integration Challenges and Solutions at a Large Research Campus

Abstract

Rich, well-organized building performance and energy consumption data enable a host of analytic capabilities for building owners and operators, from basic energy benchmarking to detailed fault detection and system optimization. Unfortunately, data integration for building control systems is challenging and costly in any setting. Large portfolios of buildings--campuses, cities, and corporate portfolios--experience these integration challenges most acutely. These large portfolios often have a wide array of control systems, including multiple vendors and nonstandard communication protocols. They typically have complex information technology (IT) networks and cybersecurity requirements and may integrate distributed energy resources into their infrastructure. Although the challenges are significant, the integration of control system data has the potential to provide proportionally greater value for these organizations through portfolio-scale analytics, comprehensive demand management, and asset performance visibility. As a large research campus, the National Renewable Energy Laboratory (NREL) experiences significant data integration challenges. To meet them, NREL has developed an architecture for effective data collection, integration, and analysis, providing a comprehensive view of data integration based on functional layers. The architecture is being evaluated on the NREL campus through deployment of three pilot implementations.

Authors:
; ; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1324228
Report Number(s):
NREL/CP-3500-67072
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2016 ACEEE Summer Study on Energy Efficiency in Buildings, 21-26 August 2016, Pacific Grove, California
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; building performance data; energy consumption; building control systems

Citation Formats

Cutler, Dylan, Frank, Stephen, Slovensky, Michelle, Sheppy, Michael, and Petersen, Anya. Creating an Energy Intelligent Campus: Data Integration Challenges and Solutions at a Large Research Campus. United States: N. p., 2016. Web.
Cutler, Dylan, Frank, Stephen, Slovensky, Michelle, Sheppy, Michael, & Petersen, Anya. Creating an Energy Intelligent Campus: Data Integration Challenges and Solutions at a Large Research Campus. United States.
Cutler, Dylan, Frank, Stephen, Slovensky, Michelle, Sheppy, Michael, and Petersen, Anya. 2016. "Creating an Energy Intelligent Campus: Data Integration Challenges and Solutions at a Large Research Campus". United States. doi:.
@article{osti_1324228,
title = {Creating an Energy Intelligent Campus: Data Integration Challenges and Solutions at a Large Research Campus},
author = {Cutler, Dylan and Frank, Stephen and Slovensky, Michelle and Sheppy, Michael and Petersen, Anya},
abstractNote = {Rich, well-organized building performance and energy consumption data enable a host of analytic capabilities for building owners and operators, from basic energy benchmarking to detailed fault detection and system optimization. Unfortunately, data integration for building control systems is challenging and costly in any setting. Large portfolios of buildings--campuses, cities, and corporate portfolios--experience these integration challenges most acutely. These large portfolios often have a wide array of control systems, including multiple vendors and nonstandard communication protocols. They typically have complex information technology (IT) networks and cybersecurity requirements and may integrate distributed energy resources into their infrastructure. Although the challenges are significant, the integration of control system data has the potential to provide proportionally greater value for these organizations through portfolio-scale analytics, comprehensive demand management, and asset performance visibility. As a large research campus, the National Renewable Energy Laboratory (NREL) experiences significant data integration challenges. To meet them, NREL has developed an architecture for effective data collection, integration, and analysis, providing a comprehensive view of data integration based on functional layers. The architecture is being evaluated on the NREL campus through deployment of three pilot implementations.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 8
}

Conference:
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