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Cited by 396

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A Distributed Demand Response Algorithm and Its Application to PHEV Charging in Smart Grids

Fan, Zhong·2012·IEEE Transactions on Smart Grid

Abstract

This paper proposes a distributed framework for demand response and user adaptation in smart grid networks. In particular, we borrow the concept of congestion pricing in Internet traffic control and show that pricing information is very useful to regulate user demand and hence balance network load. User preference is modeled as a willingness to pay parameter which can be seen as an indicator of differential quality of service. Both analysis and simulation results are presented to demonstrate the dynamics and convergence behavior of the algorithm. Based on this algorithm, we then propose a novel charging method for plug-in hybrid electric vehicles (PHEVs) in a smart grid, where users or PHEVs can adapt their charging rates according to their preferences. Simulation results are presented to demonstrate the dynamic behavior of the charging algorithm and impact of different parameters on system performance.

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Metadata

Authors
Fan, Z.
Venue
IEEE Transactions on Smart Grid
Published
2012-09
Volume
3
Issue
3
Pages
1280-1290
ISSN
  • 1949-3053 (ISSN-L)
  • 1949-3061
OpenAlex
W2062100562
Cited by
396
References
1
FWCI
26.66
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Distributed Demand Response Algorithm and Its Application to PHEV Charging in Smart Grids. https://app.cochat.ai/papers/10.1109/tsg.2012.2185075
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Fan, Z. (2012). A Distributed Demand Response Algorithm and Its Application to PHEV Charging in Smart Grids. IEEE Transactions on Smart Grid. https://doi.org/10.1109/tsg.2012.2185075

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.