Demand response capacity estimation in various supply areas
Vladimir M. Shiljkut and
Nikola Lj. Rajakovic
Energy, 2015, vol. 92, issue P3, 476-486
Abstract:
In order to apply the demand response (DR) program, the capacity for DR of the particular utility should be estimated. This paper presents an improved load profiles comparison method for the DR capacity estimation. It is based on comparison of typical daily load profiles for the same (or close) date in two years, but with different weather conditions. The consequence is that load profiles in these two cases are significantly different. Minimum and maximum values of load differences have been determined. In order to narrow the estimated DR capacity range the differences are normalized (divided with the difference in consumption for the two compared profiles). This normalization improves the comparison method and obtained results indicate more precisely the extent of available DR capacity. The method is applicable to the whole utility or to its parts, for any season. Analyses have been done on the particular case study for both winter and high summer season. The impact of day type (working days and weekend) on DR capacity estimation results has been also elaborated.
Keywords: Capacity; Demand; Estimation; Load management; Load profile; Variable generation (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544215005411
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:92:y:2015:i:p3:p:476-486
DOI: 10.1016/j.energy.2015.05.007
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().