Finding the cost-optimal mix of building energy technologies that satisfies a set operational energy reduction target

Brian Simmons; Matthias H.Y. Tan; C.F. Jeff Wu; Youngdong Yu; Godfried Augenbroe

Finding the cost-optimal mix of building energy technologies that satisfies a set operational energy reduction target

Brian Simmons
, Matthias H.Y. Tan
, C.F. Jeff Wu
, Youngdong Yu
, Godfried Augenbroe

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

5 Citations (Scopus)

Abstract

This paper presents the development of an optimization methodology for selecting the lowest monetary cost combinations of building technologies to meet set operational energy reduction targets. The developed optimization algorithm comes from the fact that the actual properties of building technologies have a discrete nature and seeing their selection as a combinatoric problem. The optimization algorithm searches the discrete combinatoric space by maximizing the objective function: calculated energy savings divided by premium cost. The algorithm is codified into a custom MATLAB script and when compared to prescriptive methodologies is shown to be much more cost effective and can be generically applied given a palette of building technology alternatives and their corresponding cost data. Copyright © 2011 by IPAC'11/EPS-AG.

Original language	English
Title of host publication	Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association
Pages	1852-1859
Publication status	Published - 2013
Externally published	Yes
Event	13th Conference of the International Building Performance Simulation Association, BS 2013 - Chambery, France Duration: 26 Aug 2013 → 28 Aug 2013

Conference

Conference	13th Conference of the International Building Performance Simulation Association, BS 2013
Place	France
City	Chambery
Period	26/08/13 → 28/08/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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@inproceedings{a0ea0451288e4575a9f08931fe839146,

title = "Finding the cost-optimal mix of building energy technologies that satisfies a set operational energy reduction target",

abstract = "This paper presents the development of an optimization methodology for selecting the lowest monetary cost combinations of building technologies to meet set operational energy reduction targets. The developed optimization algorithm comes from the fact that the actual properties of building technologies have a discrete nature and seeing their selection as a combinatoric problem. The optimization algorithm searches the discrete combinatoric space by maximizing the objective function: calculated energy savings divided by premium cost. The algorithm is codified into a custom MATLAB script and when compared to prescriptive methodologies is shown to be much more cost effective and can be generically applied given a palette of building technology alternatives and their corresponding cost data. Copyright {\textcopyright} 2011 by IPAC'11/EPS-AG.",

author = "Brian Simmons and Tan, \{Matthias H.Y.\} and Wu, \{C.F. Jeff\} and Youngdong Yu and Godfried Augenbroe",

year = "2013",

language = "English",

pages = "1852--1859",

booktitle = "Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association",

note = "13th Conference of the International Building Performance Simulation Association, BS 2013 ; Conference date: 26-08-2013 Through 28-08-2013",

}

Simmons, B, Tan, MHY, Wu, CFJ, Yu, Y & Augenbroe, G 2013, Finding the cost-optimal mix of building energy technologies that satisfies a set operational energy reduction target. in Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association. pp. 1852-1859, 13th Conference of the International Building Performance Simulation Association, BS 2013, Chambery, France, 26/08/13.

Finding the cost-optimal mix of building energy technologies that satisfies a set operational energy reduction target. / Simmons, Brian; Tan, Matthias H.Y.; Wu, C.F. Jeff et al.
Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association. 2013. p. 1852-1859.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Finding the cost-optimal mix of building energy technologies that satisfies a set operational energy reduction target

AU - Simmons, Brian

AU - Tan, Matthias H.Y.

AU - Wu, C.F. Jeff

AU - Yu, Youngdong

AU - Augenbroe, Godfried

PY - 2013

Y1 - 2013

N2 - This paper presents the development of an optimization methodology for selecting the lowest monetary cost combinations of building technologies to meet set operational energy reduction targets. The developed optimization algorithm comes from the fact that the actual properties of building technologies have a discrete nature and seeing their selection as a combinatoric problem. The optimization algorithm searches the discrete combinatoric space by maximizing the objective function: calculated energy savings divided by premium cost. The algorithm is codified into a custom MATLAB script and when compared to prescriptive methodologies is shown to be much more cost effective and can be generically applied given a palette of building technology alternatives and their corresponding cost data. Copyright © 2011 by IPAC'11/EPS-AG.

AB - This paper presents the development of an optimization methodology for selecting the lowest monetary cost combinations of building technologies to meet set operational energy reduction targets. The developed optimization algorithm comes from the fact that the actual properties of building technologies have a discrete nature and seeing their selection as a combinatoric problem. The optimization algorithm searches the discrete combinatoric space by maximizing the objective function: calculated energy savings divided by premium cost. The algorithm is codified into a custom MATLAB script and when compared to prescriptive methodologies is shown to be much more cost effective and can be generically applied given a palette of building technology alternatives and their corresponding cost data. Copyright © 2011 by IPAC'11/EPS-AG.

UR - https://www.scopus.com/pages/publications/84886651381

UR - https://www.scopus.com/pages/publications/84886651381#tab=impact

M3 - RGC 32 - Refereed conference paper (with host publication)

SP - 1852

EP - 1859

BT - Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association

T2 - 13th Conference of the International Building Performance Simulation Association, BS 2013

Y2 - 26 August 2013 through 28 August 2013

ER -

Finding the cost-optimal mix of building energy technologies that satisfies a set operational energy reduction target

Abstract

Conference

UN SDGs

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