Abstract
A novel methodology to accurately estimate the cooling demand in residential units is proposed, as a means of providing a better assessment of urban heat-island effects attributable to the use of residential air-conditioning units. The methodology integrates probabilistic variations in occupant behavior, which is shown to be a significant factor in estimated residential cooling requirements. The methodology consists of two key features. The first is an algorithm that generates short-term events that are likely to occur in a residential context, based on published data on occupant behavior. The second is a Monte Carlo approach to cooling load calculations based on stochastic variations in these short-term events and in the consequent likelihood of switching air-conditioning on or off.
| Original language | English |
|---|---|
| Pages (from-to) | 610-619 |
| Number of pages | 10 |
| Journal | Building and Environment |
| Volume | 43 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Apr 1 2008 |
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All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Civil and Structural Engineering
- Geography, Planning and Development
- Building and Construction
Cite this
A methodology for peak energy requirement considering actual variation of occupants' behavior schedules. / Tanimoto, Jun; Hagishima, Aya; Sagara, Hiroki.
In: Building and Environment, Vol. 43, No. 4, 01.04.2008, p. 610-619.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A methodology for peak energy requirement considering actual variation of occupants' behavior schedules
AU - Tanimoto, Jun
AU - Hagishima, Aya
AU - Sagara, Hiroki
PY - 2008/4/1
Y1 - 2008/4/1
N2 - A novel methodology to accurately estimate the cooling demand in residential units is proposed, as a means of providing a better assessment of urban heat-island effects attributable to the use of residential air-conditioning units. The methodology integrates probabilistic variations in occupant behavior, which is shown to be a significant factor in estimated residential cooling requirements. The methodology consists of two key features. The first is an algorithm that generates short-term events that are likely to occur in a residential context, based on published data on occupant behavior. The second is a Monte Carlo approach to cooling load calculations based on stochastic variations in these short-term events and in the consequent likelihood of switching air-conditioning on or off.
AB - A novel methodology to accurately estimate the cooling demand in residential units is proposed, as a means of providing a better assessment of urban heat-island effects attributable to the use of residential air-conditioning units. The methodology integrates probabilistic variations in occupant behavior, which is shown to be a significant factor in estimated residential cooling requirements. The methodology consists of two key features. The first is an algorithm that generates short-term events that are likely to occur in a residential context, based on published data on occupant behavior. The second is a Monte Carlo approach to cooling load calculations based on stochastic variations in these short-term events and in the consequent likelihood of switching air-conditioning on or off.
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UR - http://www.scopus.com/inward/citedby.url?scp=36549023402&partnerID=8YFLogxK
U2 - 10.1016/j.buildenv.2006.06.034
DO - 10.1016/j.buildenv.2006.06.034
M3 - Article
AN - SCOPUS:36549023402
VL - 43
SP - 610
EP - 619
JO - Building and Environment
JF - Building and Environment
SN - 0360-1323
IS - 4
ER -