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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao IEEE Systems Journalarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
IEEE Systems Journal
Article . 2021 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Risk-Constrained Bidding Strategy for Demand Response, Green Energy Resources, and Plug-In Electric Vehicle in a Flexible Smart Grid

Authors: Masoud Rashidinejad; Peyman Afzali; Amir Abdollahi; Alireza Bakhshai;

Risk-Constrained Bidding Strategy for Demand Response, Green Energy Resources, and Plug-In Electric Vehicle in a Flexible Smart Grid

Abstract

The flexibility of smart grids has become an important issue due to the increasing penetration of uncertain energy resources, such as renewable as well as virtual power plants in the smart grids. Flexibility sources, such as demand response (DR) programs and plug-in electric vehicles (PEVs), can help the smart grid to be more productive. Although the renewable power plants are considered as flexible tools, they are somehow uncertain by themselves. In this article, the uncertainty of power generation of renewable resources has been resolved by incorporating the DR programs and PEVs. A stochastic decision making model for the coordinated operation of renewable resources and some virtual power generation is presented to solve a risk-constrained optimal bidding strategy for a smart grid. The participation of DR and PEV aggregators in the day-ahead market is considered. The uncertainty in day-ahead prices associated with renewable power generation is discussed throughout this article. As a well-known measure, the conditional value at risk is employed in the model to cope with all aforementioned uncertainties. Numerical studies and result analysis show that the expected profit of these resources is increased and the related risk is reduced significantly.

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
31
Top 10%
Top 10%
Top 10%