Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/90253
Title: Optimal operation of multimicrogrids via cooperative energy and reserve scheduling
Authors: Li, Yuanzheng
Zhao, Tianyang
Wang, Ping
Gooi, Hoay Beng
Wu, Lei
Liu, Yun
Ye, Jian
Keywords: DRNTU::Engineering::Computer science and engineering
Energy And Reserve
Cooperative Scheduling Model
Issue Date: 2018
Source: Li, Y., Zhao, T., Wang, P., Gooi, H. B., Wu, L., Liu, Y., & Ye, J. (2018). Optimal operation of multimicrogrids via cooperative energy and reserve scheduling. IEEE Transactions on Industrial Informatics, 14(8), 3459-3468. doi:10.1109/TII.2018.2792441
Series/Report no.: IEEE Transactions on Industrial Informatics
Abstract: Microgrid (MG) represents one of the major drives of adopting Internet of Things for smart cities, as it effectively integrates various distributed energy resources. Indeed, MGs can be connected with each other and presented as a system of multimicrogrid (MMG). This paper proposes the optimal operation of MMGs by a cooperative energy and reserve scheduling model, in which energy and reserve can be cooperatively utilized among MMGs. In addition, values of Shapely are introduced to allocate economic benefits of the cooperative operation. Finally, a case study based on a system of MMGs is conducted, and simulation results verify the effectiveness of the proposed cooperative scheduling model.
URI: https://hdl.handle.net/10356/90253
http://hdl.handle.net/10220/48462
ISSN: 1551-3203
DOI: 10.1109/TII.2018.2792441
Schools: School of Computer Science and Engineering 
School of Electrical and Electronic Engineering 
Research Centres: Energy Research Institute @ NTU (ERI@N) 
Rights: © 2018 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.2018.2792441
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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