Cooperative bidding-based robust optimal energy management of multimicrogrids
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 constit...
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sg-ntu-dr.10356-1420372020-06-15T03:55:05Z Cooperative bidding-based robust optimal energy management of multimicrogrids Sampath, Lahanda Purage Mohasha Isuru Krishnan, Ashok Foo, Eddy Yi Shyh Gooi, Hoay Beng School of Electrical and Electronic Engineering Interdisciplinary Graduate School (IGS) Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution Day-ahead Planning Distributed Optimization 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. MOE (Min. of Education, S’pore) Accepted version 2020-06-15T03:55:05Z 2020-06-15T03:55:05Z 2019 Journal Article 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 1551-3203 https://hdl.handle.net/10356/142037 10.1109/TII.2019.2955991 9 16 5757 5768 en 2018-T1-002-093 IEEE Transactions on Industrial Informatics © 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: https://doi.org/10.1109/TII.2019.2955991. application/pdf |
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Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution Day-ahead Planning Distributed Optimization Sampath, Lahanda Purage Mohasha Isuru Krishnan, Ashok Foo, Eddy Yi Shyh Gooi, Hoay Beng Cooperative bidding-based robust optimal energy management of multimicrogrids |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Sampath, Lahanda Purage Mohasha Isuru Krishnan, Ashok Foo, Eddy Yi Shyh Gooi, Hoay Beng |
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Article |
author |
Sampath, Lahanda Purage Mohasha Isuru Krishnan, Ashok Foo, Eddy Yi Shyh Gooi, Hoay Beng |
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Sampath, Lahanda Purage Mohasha Isuru |
title |
Cooperative bidding-based robust optimal energy management of multimicrogrids |
title_short |
Cooperative bidding-based robust optimal energy management of multimicrogrids |
title_full |
Cooperative bidding-based robust optimal energy management of multimicrogrids |
title_fullStr |
Cooperative bidding-based robust optimal energy management of multimicrogrids |
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Cooperative bidding-based robust optimal energy management of multimicrogrids |
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cooperative bidding-based robust optimal energy management of multimicrogrids |
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2020 |
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https://hdl.handle.net/10356/142037 |
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