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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 Transactions on...arrow_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 Transactions on Industry Applications
Article . 2021 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Multi-timescale Active Distribution Network Scheduling Considering Demand Response and User Comprehensive Satisfaction

Authors: orcid bw Hongzhang Sheng;
Hongzhang Sheng
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Hongzhang Sheng in OpenAIRE
orcid bw Chengfu Wang;
Chengfu Wang
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Derived by OpenAIRE algorithms or harvested from 3rd party repositories

Chengfu Wang in OpenAIRE
Bowen Li; Jun Liang; orcid Ming Yang;
Ming Yang
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Ming Yang in OpenAIRE
Yunhui Dong;

Multi-timescale Active Distribution Network Scheduling Considering Demand Response and User Comprehensive Satisfaction

Abstract

A large number of distributed energy resources (DERs) integrate into the distribution network, which changes the power flow, increases the power fluctuations, and complicates the scheduling of the distribution network. To cope with that, a multitimescale scheduling method, which considers the demand response as well as user satisfaction, is proposed in this paper. First, in the day-ahead stage, both the generation-side and demand-side are combined to minimize the operating costs and reduce the impact of DERs. Second, in the real-time stage, the model predictive control method is introduced, smoothing the power fluctuations and maximizing the consumed renewable energy. Finally, the user comprehensive satisfaction is considered, ensuring the users’ benefit and improving the flexibility of users to participate in scheduling while shifting electricity demands. By optimizing the generation-side and demand-side on both day-ahead and real-time timescales, the proposed method can improve the operation status for the distribution network effectively while ensuring the interests of users. Simulation on an improved IEEE-33 bus distribution system verifies the effectiveness of the proposed method.

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