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Title: Cooperative bidding-based robust optimal energy management of multimicrogrids
Authors: Sampath, Lahanda Purage Mohasha Isuru
Krishnan, Ashok
Foo, Eddy Yi Shyh
Gooi, Hoay Beng
Keywords: Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution
Issue Date: 2019
Source: Sampath, L. P. M. I., Krishnan, A., Foo, E. Y. S., & Gooi, H. B. (2020). Cooperative bidding-based robust optimal energy management of multimicrogrids. IEEE Transactions on Industrial Informatics, 16(9), 5757-5768. doi:10.1109/TII.2019.2955991
Project: 2018-T1-002-093
Journal: IEEE Transactions on Industrial Informatics
Abstract: The increasing penetration of renewable energy sources (RESs) has led to the proliferation of microgrids (MGs) in the power system. Recently, the concept of multimicrogrid (MMG) systems has come into prominence due to the economic benefits accrued through the sharing of resources between the constituent MGs. The uncertainties caused by the penetration of RESs necessitate the usage of advanced optimization procedures to manage the MMG system. This article proposes a robust optimization (RO) framework to determine the day-ahead schedule of an MMG system. Unlike the existing works in the literature, the proposed RO framework preserves the nonanticipativity in reserve scheduling. The proposed RO framework also includes a cooperative bidding-based trading scheme to facilitate the sharing of energy and reserves between the constituent MGs in the MMG system. The results highlight the economic benefits obtained through the sharing of resources between the constituent MGs in an MMG system. Furthermore, the results also demonstrate that the proposed nonanticipative RO framework performs better in terms of robustness when compared with the existing RO frameworks for MMG systems in the literature.
ISSN: 1551-3203
DOI: 10.1109/TII.2019.2955991
Rights: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at:
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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