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U.S. Department of Energy
Office of Scientific and Technical Information

Using EMIS to Identify Top Opportunities for Commercial Building Efficiency

Technical Report ·
DOI:https://doi.org/10.2172/1350976· OSTI ID:1350976
 [1];  [1];  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Energy Management and Information Systems (EMIS) comprise a broad family of tools and services to manage commercial building energy use. These technologies offer a mix of capabilities to store, display, and analyze energy use and system data, and in some cases, provide control. EMIS technologies enable 10–20 percent site energy savings in best practice implementations. Energy Information System (EIS) and Fault Detection and Diagnosis (FDD) systems are two key technologies in the EMIS family. Energy Information Systems are broadly defined as the web-based software, data acquisition hardware, and communication systems used to analyze and display building energy performance. At a minimum, an EIS provides daily, hourly or sub-hourly interval meter data at the whole-building level, with graphical and analytical capability. Fault Detection and Diagnosis systems automatically identify heating, ventilation, and air-conditioning (HVAC) system or equipment-level performances issues, and in some cases are able to isolate the root causes of the problem. They use computer algorithms to continuously analyze system-level operational data to detect faults and diagnose their causes. Many FDD tools integrate the trend log data from a Building Automation System (BAS) but otherwise are stand-alone software packages; other types of FDD tools are implemented as “on-board” equipment-embedded diagnostics. (This document focuses on the former.) Analysis approaches adopted in FDD technologies span a variety of techniques from rule-based methods to process history-based approaches. FDD tools automate investigations that can be conducted via manual data inspection by someone with expert knowledge, thereby expanding accessibility and breath of analysis opportunity, and also reducing complexity.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies Office (EE-3B)
DOE Contract Number:
AC02-05CH11231
OSTI ID:
1350976
Report Number(s):
LBNL--1007250; ir:1007250
Country of Publication:
United States
Language:
English

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