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Methodology for adapting rigorous si...

Sun, Jian.

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Methodology for adapting rigorous simulation programs to supervisory control of building HVAC&R systems: Simulation, calibration and optimization.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Methodology for adapting rigorous simulation programs to supervisory control of building HVAC&R systems: Simulation, calibration and optimization./
Author:	Sun, Jian.
Description:	134 p.
Notes:	Source: Dissertation Abstracts International, Volume: 65-11, Section: B, page: 6018.
Contained By:	Dissertation Abstracts International65-11B.
Subject:	Engineering, Civil. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3154165
ISBN:	9780496150038

Methodology for adapting rigorous simulation programs to supervisory control of building HVAC&R systems: Simulation, calibration and optimization.
Sun, Jian.

Methodology for adapting rigorous simulation programs to supervisory control of building HVAC&R systems: Simulation, calibration and optimization. - 134 p.

Source: Dissertation Abstracts International, Volume: 65-11, Section: B, page: 6018.

Thesis (Ph.D.)--Drexel University, 2004.

In this thesis, general and systematic methodologies were developed for simulating, calibrating and optimal control of building energy system. Based on investigation of two popular system simulation approaches, Sequential Component Method (SCM) and Equation-Oriented Method (EOM), a hybrid simulation strategy, named Successive Approximation Method (SAM), was proposed for combining some of the desirable features of both SCM and EOM. SAM is a more coherent strategy which involves two aspects: (i) formulation of the Successive Approximation Method, and (ii) using the automatic differentiation (AD) technique to compute the Jacobian matrix. A systematic calibration approach, named analytic optimization approach, was developed as a means of performing a guided refined search during the calibration of detailed building energy simulation programs. This includes four basic elements: sensitivity analysis, identifiability analysis, numerical optimization, and uncertainty analysis. This study also presents a general and systematic methodology, termed Complete Simulation Based Sequential Quadratic Programming (CSB-SQP), for determining the optimal control of building energy systems. We develop the mathematical basis of the methodology and apply it to a simple cooling plant system to illustrate the accuracy, efficiency and robustness of this method.

ISBN: 9780496150038Subjects--Topical Terms:

783781
Engineering, Civil.

Methodology for adapting rigorous simulation programs to supervisory control of building HVAC&R systems: Simulation, calibration and optimization.
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100 1 $a Sun, Jian. $3 1031963
245 1 0 $a Methodology for adapting rigorous simulation programs to supervisory control of building HVAC&R systems: Simulation, calibration and optimization.
300 $a 134 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-11, Section: B, page: 6018.
500 $a Adviser: Agami Reddy.
502 $a Thesis (Ph.D.)--Drexel University, 2004.
520 $a In this thesis, general and systematic methodologies were developed for simulating, calibrating and optimal control of building energy system. Based on investigation of two popular system simulation approaches, Sequential Component Method (SCM) and Equation-Oriented Method (EOM), a hybrid simulation strategy, named Successive Approximation Method (SAM), was proposed for combining some of the desirable features of both SCM and EOM. SAM is a more coherent strategy which involves two aspects: (i) formulation of the Successive Approximation Method, and (ii) using the automatic differentiation (AD) technique to compute the Jacobian matrix. A systematic calibration approach, named analytic optimization approach, was developed as a means of performing a guided refined search during the calibration of detailed building energy simulation programs. This includes four basic elements: sensitivity analysis, identifiability analysis, numerical optimization, and uncertainty analysis. This study also presents a general and systematic methodology, termed Complete Simulation Based Sequential Quadratic Programming (CSB-SQP), for determining the optimal control of building energy systems. We develop the mathematical basis of the methodology and apply it to a simple cooling plant system to illustrate the accuracy, efficiency and robustness of this method.
590 $a School code: 0065.
650 4 $a Engineering, Civil. $3 783781
650 4 $a Engineering, Mechanical. $3 783786
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710 2 0 $a Drexel University. $3 1018434
773 0 $t Dissertation Abstracts International $g 65-11B.
790 1 0 $a Reddy, Agami, $e advisor
790 $a 0065
791 $a Ph.D.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3154165