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Title: Fuzzy Linguistic Knowledge Based Behavior Extraction for Building Energy Management Systems

Significant portion of world energy production is consumed by building Heating, Ventilation and Air Conditioning (HVAC) units. Thus along with occupant comfort, energy efficiency is also an important factor in HVAC control. Modern buildings use advanced Multiple Input Multiple Output (MIMO) control schemes to realize these goals. However, since the performance of HVAC units is dependent on many criteria including uncertainties in weather, number of occupants, and thermal state, the performance of current state of the art systems are sub-optimal. Furthermore, because of the large number of sensors in buildings, and the high frequency of data collection, large amount of information is available. Therefore, important behavior of buildings that compromise energy efficiency or occupant comfort is difficult to identify. This paper presents an easy to use and understandable framework for identifying such behavior. The presented framework uses human understandable knowledge-base to extract important behavior of buildings and present it to users via a graphical user interface. The presented framework was tested on a building in the Pacific Northwest and was shown to be able to identify important behavior that relates to energy efficiency and occupant comfort.
Authors:
;
Publication Date:
OSTI Identifier:
1097187
Report Number(s):
INL/CON-13-29197
DOE Contract Number:
DE-AC07-05ID14517
Resource Type:
Conference
Resource Relation:
Conference: 6th International Symposium on Resilient Control Systems,San Francisco, CA,08/13/2013,08/16/2013
Research Org:
Idaho National Laboratory (INL)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 97 MATHEMATICS AND COMPUTING HVAC; building energy efficiency; building occupan