A statistical model for natural gas standardized load profiles
AbstractWe present a statistical model for construction and application of standardized load profiles. Standardized load profile curves give a typical natural gas consumption pattern throughout a year in various time resolutions. Our semiparametric regression model uses three types of information, constant characteristics of an individual customer, individual historical consumption and time varying explanatory variables, both to describe typical trend and to correct for departure of current conditions from normal. The model's multiplicative structure allows for convenient separation of individual-specific and common time varying parts. Although corrections are parametric, no substantial information about the typical consumption trend is available, so it is modelled non-parametrically. Corrections for temperature effects are non-linear; hence we deal with them through an obvious extension of the generalized additive model framework. Copyright (c) 2009 Royal Statistical Society.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series C (Applied Statistics).
Volume (Year): 58 (2009)
Issue (Month): 1 ()
Contact details of provider:
Postal: 12 Errol Street, London EC1Y 8LX, United Kingdom
Web page: http://www.blackwellpublishing.com/journal.asp?ref=0035-9254
More information through EDIRC
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.