Fuzzy Linguistic Knowledge Based Behavior Extraction for Building Energy Management Systems

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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 … continued below

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Wijayasekara, Dumidu & Manic, Milos August 1, 2013.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by the UNT Libraries Government Documents Department to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 54 times. More information about this article can be viewed below.

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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.

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  • 6th International Symposium on Resilient Control Systems,San Francisco, CA,08/13/2013,08/16/2013

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  • Report No.: INL/CON-13-29197
  • Grant Number: DE-AC07-05ID14517
  • Office of Scientific & Technical Information Report Number: 1097187
  • Archival Resource Key: ark:/67531/metadc828016

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  • August 1, 2013

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  • May 19, 2016, 9:45 a.m.

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  • Dec. 5, 2016, 4:33 p.m.

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Wijayasekara, Dumidu & Manic, Milos. Fuzzy Linguistic Knowledge Based Behavior Extraction for Building Energy Management Systems, article, August 1, 2013; Idaho Falls, Idaho. (https://digital.library.unt.edu/ark:/67531/metadc828016/: accessed August 14, 2026), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.

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