Residential demand response scheme based on adaptive consumption level pricing
Haider Tarish Haider,
Ong Hang See and
Wilfried Elmenreich
Energy, 2016, vol. 113, issue C, 301-308
Abstract:
Demand response aims to change the energy consumption patterns of normal customers in response to changes in price rate or incentive offers. This process reduces peak loads and in turn potentially lowers the energy cost for customers. In this study, we propose a new demand response scheme on the basis of an adaptive consumption level pricing scheme. On the one hand, this strategy encourages customers to manage their energy consumption and consequently lower their energy bill. On the other hand, it allows utilities to manage the aggregate consumption and predict load requirement. Unlike other pricing schemes, such as block tariff and time-of-use, the proposed pricing scheme can lower the energy bill of about 73% of customers, assuming that the total utility revenue is the same for all pricing schemes. On the basis of the currently available schemes in the literature, we find that the proposed method has significant advantages over other schemes in terms of fairness in charging customers.
Keywords: Smart grids; Demand side management; Residential demand response; Advance metering infrastructure (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544216309768
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:113:y:2016:i:c:p:301-308
DOI: 10.1016/j.energy.2016.07.052
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 ().