Intelligent optimal control of thermal comfort using response surface method

Akihiro Kato; Toshiharu Ikaga; Shuzo Murakami; Hiroaki Tsutsui; Haruka Ueda

Intelligent optimal control of thermal comfort using response surface method

Akihiro Kato, Toshiharu Ikaga, Shuzo Murakami, Hiroaki Tsutsui, Haruka Ueda

Department of System Design Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

Optimal control of HVAC system is required because of its considerable influence on workplace-productivity, health and global environment. In this study, we developed an optimal HVAC control system using Response Surface Method by Spline, which calculates optimal control conditions on the basis of cause-and-effect model of thermal comfort, outdoor environment and control parameters created by building's operational data. Experimental study was conducted to verify the effectiveness of developed method by applying it on optimization problem of thermal comfort in several zones. We concluded that our method is practicable and efficient to achieve multi-objective optimization control on HVAC system.

Original language	English
Publication status	Published - 2009
Event	9th International Healthy Buildings Conference and Exhibition, HB 2009 - Syracuse, NY, United States Duration: 2009 Sept 13 → 2009 Sept 17

Other

Other	9th International Healthy Buildings Conference and Exhibition, HB 2009
Country/Territory	United States
City	Syracuse, NY
Period	09/9/13 → 09/9/17

Keywords

Leaning ability
Optimization
Predicted Mean Vote
Response Surface Method
Variable air volume

ASJC Scopus subject areas

Civil and Structural Engineering
Building and Construction

Cite this

@conference{9a7ec680a89c4e35b9167d23c1145dca,

title = "Intelligent optimal control of thermal comfort using response surface method",

abstract = "Optimal control of HVAC system is required because of its considerable influence on workplace-productivity, health and global environment. In this study, we developed an optimal HVAC control system using Response Surface Method by Spline, which calculates optimal control conditions on the basis of cause-and-effect model of thermal comfort, outdoor environment and control parameters created by building's operational data. Experimental study was conducted to verify the effectiveness of developed method by applying it on optimization problem of thermal comfort in several zones. We concluded that our method is practicable and efficient to achieve multi-objective optimization control on HVAC system.",

keywords = "Leaning ability, Optimization, Predicted Mean Vote, Response Surface Method, Variable air volume",

author = "Akihiro Kato and Toshiharu Ikaga and Shuzo Murakami and Hiroaki Tsutsui and Haruka Ueda",

year = "2009",

language = "English",

}

TY - CONF

T1 - Intelligent optimal control of thermal comfort using response surface method

AU - Kato, Akihiro

AU - Ikaga, Toshiharu

AU - Murakami, Shuzo

AU - Tsutsui, Hiroaki

AU - Ueda, Haruka

PY - 2009

Y1 - 2009

N2 - Optimal control of HVAC system is required because of its considerable influence on workplace-productivity, health and global environment. In this study, we developed an optimal HVAC control system using Response Surface Method by Spline, which calculates optimal control conditions on the basis of cause-and-effect model of thermal comfort, outdoor environment and control parameters created by building's operational data. Experimental study was conducted to verify the effectiveness of developed method by applying it on optimization problem of thermal comfort in several zones. We concluded that our method is practicable and efficient to achieve multi-objective optimization control on HVAC system.

AB - Optimal control of HVAC system is required because of its considerable influence on workplace-productivity, health and global environment. In this study, we developed an optimal HVAC control system using Response Surface Method by Spline, which calculates optimal control conditions on the basis of cause-and-effect model of thermal comfort, outdoor environment and control parameters created by building's operational data. Experimental study was conducted to verify the effectiveness of developed method by applying it on optimization problem of thermal comfort in several zones. We concluded that our method is practicable and efficient to achieve multi-objective optimization control on HVAC system.

KW - Leaning ability

KW - Optimization

KW - Predicted Mean Vote

KW - Response Surface Method

KW - Variable air volume

UR - http://www.scopus.com/inward/record.url?scp=84872652217&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84872652217&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:84872652217

T2 - 9th International Healthy Buildings Conference and Exhibition, HB 2009

Y2 - 13 September 2009 through 17 September 2009

ER -

Intelligent optimal control of thermal comfort using response surface method

Abstract

Other

Keywords

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this