dc.contributor.author |
Ye, Xianming
|
|
dc.contributor.author |
Xia, Xiaohua
|
|
dc.contributor.author |
Zhang, Jiangfeng
|
|
dc.date.accessioned |
2014-02-20T11:54:47Z |
|
dc.date.available |
2014-02-20T11:54:47Z |
|
dc.date.issued |
2013 |
|
dc.description.abstract |
Clean development mechanism (CDM) project developers are always interested in achieving required
measurement accuracies with the least metering cost. In this paper, a metering cost minimisation model
is proposed for the sampling plan of a specific CDM energy efficiency lighting project. The problem arises
from the particular CDM sampling requirement of 90% confidence and 10% precision for the small-scale
CDM energy efficiency projects, which is known as the 90/10 criterion. The 90/10 criterion can be met
through solving the metering cost minimisation problem. All the lights in the project are classified into
different groups according to uncertainties of the lighting energy consumption, which are characterised
by their statistical coefficient of variance (CV). Samples from each group are randomly selected to install
power meters. These meters include less expensive ones with less functionality and more expensive ones
with greater functionality. The metering cost minimisation model will minimise the total metering cost
through the determination of the optimal sample size at each group. The 90/10 criterion is formulated as
constraints to the metering cost objective. The optimal solution to the minimisation problem will therefore
minimise the metering cost whilst meeting the 90/10 criterion, and this is verified by a case study.
Relationships between the optimal metering cost and the population sizes of the groups, CV values and
the meter equipment cost are further explored in three simulations. The metering cost minimisation
model proposed for lighting systems is applicable to other CDM projects as well. |
en_US |
dc.description.librarian |
hb2014 |
en_US |
dc.description.sponsorship |
The National Hub for the Postgraduate
Programme in Energy Efficiency and Demand Side Management
at the University of Pretoria. |
en_US |
dc.description.uri |
http://www.elsevier.com/ locate/apenergy |
en_US |
dc.identifier.citation |
Ye, X, Xia, X & Zhang, J 2013, 'Optimal sampling plan for clean development mechanism energy efficiency lighting projects', Applied Energy , vol. 112, no. 12, pp. 1006-1015. |
en_US |
dc.identifier.issn |
0306-2619 (print) |
|
dc.identifier.issn |
1872-9118 (online) |
|
dc.identifier.other |
10.1016/j.apenergy.2013.05.064 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/34636 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
Elsevier |
en_US |
dc.rights |
© 2013 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Applied Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Applied Energy, vol. 112, no. 12, pp.1006-1015,2013. doi : 10.1016/j.apenergy.2013.05.064 |
en_US |
dc.subject |
Sample size determination |
en_US |
dc.subject |
Energy efficiency |
en_US |
dc.subject |
Lighting |
en_US |
dc.subject |
Clean development mechanism (CDM) |
en_US |
dc.title |
Optimal sampling plan for clean development mechanism energy efficiency lighting projects |
en_US |
dc.type |
Postprint Article |
en_US |