Correlating Probabilistic Climate Projections With Cooling Demand in an Office Building

Sandhya Patidar; David P Jenkins; Gavin Jarvis Gibson; Phillip Frank Gower Banfill

Correlating Probabilistic Climate Projections With Cooling Demand in an Office Building

Sandhya Patidar, David P Jenkins, Gavin Jarvis Gibson, Phillip Frank Gower Banfill

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Given thousands of probabilistic climate projections available through UK Climate Projections (UKCP09), currently it is difficult to quantify the effect of climate change on the energy demand and operation of a building by means of dynamic building software packages such as ESP-r. This study offers a practically efficient technique to correlate these probabilistic climate projections with hourly cooling-demand profiles for a case study – a mechanically cooled office building. A regression model has been developed and validated to examine, possibility of the cooling plant failing and influence of two simple adaptation techniques in the given building with projected future climate change.

Original language	English
Title of host publication	BSO 2012 Proceedings
Publisher	IBPSA
Pages	261-268
Number of pages	8
Publication status	Published - 10 Sept 2012
Event	1st Building Simulation and Optimization Conference 2012 - Loughborough University, Loughborough, United Kingdom Duration: 10 Sept 2012 → 11 Sept 2012

Conference

Conference	1st Building Simulation and Optimization Conference 2012
Country/Territory	United Kingdom
City	Loughborough
Period	10/09/12 → 11/09/12

UN SDGs

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

Cite this

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title = "Correlating Probabilistic Climate Projections With Cooling Demand in an Office Building",

abstract = "Given thousands of probabilistic climate projections available through UK Climate Projections (UKCP09), currently it is difficult to quantify the effect of climate change on the energy demand and operation of a building by means of dynamic building software packages such as ESP-r. This study offers a practically efficient technique to correlate these probabilistic climate projections with hourly cooling-demand profiles for a case study – a mechanically cooled office building. A regression model has been developed and validated to examine, possibility of the cooling plant failing and influence of two simple adaptation techniques in the given building with projected future climate change.",

author = "Sandhya Patidar and Jenkins, {David P} and Gibson, {Gavin Jarvis} and Banfill, {Phillip Frank Gower}",

year = "2012",

month = sep,

day = "10",

language = "English",

pages = "261--268",

booktitle = "BSO 2012 Proceedings",

publisher = "IBPSA",

address = "United Kingdom",

note = "1st Building Simulation and Optimization Conference 2012 ; Conference date: 10-09-2012 Through 11-09-2012",

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TY - GEN

T1 - Correlating Probabilistic Climate Projections With Cooling Demand in an Office Building

AU - Patidar, Sandhya

AU - Jenkins, David P

AU - Gibson, Gavin Jarvis

AU - Banfill, Phillip Frank Gower

PY - 2012/9/10

Y1 - 2012/9/10

N2 - Given thousands of probabilistic climate projections available through UK Climate Projections (UKCP09), currently it is difficult to quantify the effect of climate change on the energy demand and operation of a building by means of dynamic building software packages such as ESP-r. This study offers a practically efficient technique to correlate these probabilistic climate projections with hourly cooling-demand profiles for a case study – a mechanically cooled office building. A regression model has been developed and validated to examine, possibility of the cooling plant failing and influence of two simple adaptation techniques in the given building with projected future climate change.

AB - Given thousands of probabilistic climate projections available through UK Climate Projections (UKCP09), currently it is difficult to quantify the effect of climate change on the energy demand and operation of a building by means of dynamic building software packages such as ESP-r. This study offers a practically efficient technique to correlate these probabilistic climate projections with hourly cooling-demand profiles for a case study – a mechanically cooled office building. A regression model has been developed and validated to examine, possibility of the cooling plant failing and influence of two simple adaptation techniques in the given building with projected future climate change.

M3 - Conference contribution

SP - 261

EP - 268

BT - BSO 2012 Proceedings

PB - IBPSA

T2 - 1st Building Simulation and Optimization Conference 2012

Y2 - 10 September 2012 through 11 September 2012

ER -

Correlating Probabilistic Climate Projections With Cooling Demand in an Office Building

Abstract

Conference

UN SDGs

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