Engineering uncertainty analysis in the evaluation of energy and cost savings of cooling system alternatives based on field-monitored data

T Agami Reddy, Jeff S. Haberl, James S. Elleson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

The objective of this paper is to present a methodology and pertinent equations for performing an engineering uncertainty analysis on the savings due to a particular energy conservation measure (ECM) as compared to a baseline system. Though this study is geared toward building cooling systems, the methodology can be applied with minor modification to most building measurement and verification programs that involve performing measurements of the system, identifying a regression model, and using the model to extrapolate for future behavior once the ECM has been implemented. The methodology covers the case in which a nested model is used, as when short-term data are used to develop a model for building secondary thermal loads, which is then used to drive a model for chiller electricity use. Hence, the methodology treats measurement errors, model internal prediction uncertainty, and model extrapolation bias uncertainty in the framework of a nested model approach. A notable feature of this paper is that a nomograph, consisting of six separate interlinked graphs, has been generated based on the equations presented herein, whereby a user can graphically determine the final uncertainty in savings by selecting appropriate values of the various sources of uncertainty. The use of this nomograph is explained by means of an example.

Original languageEnglish (US)
Title of host publicationASHRAE Transactions
PublisherASHRAE
Volume105
StatePublished - 1999
Externally publishedYes
EventASHRAE Annual Meeting - Seattle, WA, USA
Duration: Jun 18 1999Jun 23 1999

Other

OtherASHRAE Annual Meeting
CitySeattle, WA, USA
Period6/18/996/23/99

Fingerprint

Uncertainty analysis
Cooling systems
Costs
Nomograms
Energy conservation
Thermal load
Measurement errors
Extrapolation
Electricity
Uncertainty

ASJC Scopus subject areas

  • Fluid Flow and Transfer Processes

Cite this

Engineering uncertainty analysis in the evaluation of energy and cost savings of cooling system alternatives based on field-monitored data. / Reddy, T Agami; Haberl, Jeff S.; Elleson, James S.

ASHRAE Transactions. Vol. 105 ASHRAE, 1999.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Reddy, TA, Haberl, JS & Elleson, JS 1999, Engineering uncertainty analysis in the evaluation of energy and cost savings of cooling system alternatives based on field-monitored data. in ASHRAE Transactions. vol. 105, ASHRAE, ASHRAE Annual Meeting, Seattle, WA, USA, 6/18/99.
@inproceedings{b1e7b5a7a90244dd9f7ff4c1269c4f4f,
title = "Engineering uncertainty analysis in the evaluation of energy and cost savings of cooling system alternatives based on field-monitored data",
abstract = "The objective of this paper is to present a methodology and pertinent equations for performing an engineering uncertainty analysis on the savings due to a particular energy conservation measure (ECM) as compared to a baseline system. Though this study is geared toward building cooling systems, the methodology can be applied with minor modification to most building measurement and verification programs that involve performing measurements of the system, identifying a regression model, and using the model to extrapolate for future behavior once the ECM has been implemented. The methodology covers the case in which a nested model is used, as when short-term data are used to develop a model for building secondary thermal loads, which is then used to drive a model for chiller electricity use. Hence, the methodology treats measurement errors, model internal prediction uncertainty, and model extrapolation bias uncertainty in the framework of a nested model approach. A notable feature of this paper is that a nomograph, consisting of six separate interlinked graphs, has been generated based on the equations presented herein, whereby a user can graphically determine the final uncertainty in savings by selecting appropriate values of the various sources of uncertainty. The use of this nomograph is explained by means of an example.",
author = "Reddy, {T Agami} and Haberl, {Jeff S.} and Elleson, {James S.}",
year = "1999",
language = "English (US)",
volume = "105",
booktitle = "ASHRAE Transactions",
publisher = "ASHRAE",

}

TY - GEN

T1 - Engineering uncertainty analysis in the evaluation of energy and cost savings of cooling system alternatives based on field-monitored data

AU - Reddy, T Agami

AU - Haberl, Jeff S.

AU - Elleson, James S.

PY - 1999

Y1 - 1999

N2 - The objective of this paper is to present a methodology and pertinent equations for performing an engineering uncertainty analysis on the savings due to a particular energy conservation measure (ECM) as compared to a baseline system. Though this study is geared toward building cooling systems, the methodology can be applied with minor modification to most building measurement and verification programs that involve performing measurements of the system, identifying a regression model, and using the model to extrapolate for future behavior once the ECM has been implemented. The methodology covers the case in which a nested model is used, as when short-term data are used to develop a model for building secondary thermal loads, which is then used to drive a model for chiller electricity use. Hence, the methodology treats measurement errors, model internal prediction uncertainty, and model extrapolation bias uncertainty in the framework of a nested model approach. A notable feature of this paper is that a nomograph, consisting of six separate interlinked graphs, has been generated based on the equations presented herein, whereby a user can graphically determine the final uncertainty in savings by selecting appropriate values of the various sources of uncertainty. The use of this nomograph is explained by means of an example.

AB - The objective of this paper is to present a methodology and pertinent equations for performing an engineering uncertainty analysis on the savings due to a particular energy conservation measure (ECM) as compared to a baseline system. Though this study is geared toward building cooling systems, the methodology can be applied with minor modification to most building measurement and verification programs that involve performing measurements of the system, identifying a regression model, and using the model to extrapolate for future behavior once the ECM has been implemented. The methodology covers the case in which a nested model is used, as when short-term data are used to develop a model for building secondary thermal loads, which is then used to drive a model for chiller electricity use. Hence, the methodology treats measurement errors, model internal prediction uncertainty, and model extrapolation bias uncertainty in the framework of a nested model approach. A notable feature of this paper is that a nomograph, consisting of six separate interlinked graphs, has been generated based on the equations presented herein, whereby a user can graphically determine the final uncertainty in savings by selecting appropriate values of the various sources of uncertainty. The use of this nomograph is explained by means of an example.

UR - http://www.scopus.com/inward/record.url?scp=0033308399&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033308399&partnerID=8YFLogxK

M3 - Conference contribution

VL - 105

BT - ASHRAE Transactions

PB - ASHRAE

ER -