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 |
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Pages (from-to) | 610-619 |
Number of pages | 10 |
Journal | Building and Environment |
Volume | 43 |
Issue number | 4 |
DOIs | |
Publication status | Published - Apr 2008 |
All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Civil and Structural Engineering
- Geography, Planning and Development
- Building and Construction