Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148382
Title: Framework for network-constrained cooperative trading of multi-microgrid systems
Authors: Isuru, Mohasha
Krishnan, Ashok
Foo, Eddy Yi Shyh
Gooi, Hoay Beng
Keywords: Engineering::Electrical and electronic engineering::Electric power
Issue Date: 2020
Source: Isuru, M., Krishnan, A., Foo, E. Y. S. & Gooi, H. B. (2020). Framework for network-constrained cooperative trading of multi-microgrid systems. 2020 59th IEEE Conference on Decision and Control (CDC). https://dx.doi.org/10.1109/CDC42340.2020.9304376
Conference: 2020 59th IEEE Conference on Decision and Control (CDC)
Abstract: The rising penetration of renewable energy sources (RESs) has led to increased research interest in the optimal scheduling and management of multi-microgrid (MMG) systems. This is due to the potential economic benefits which can be derived from the sharing of resources between the MGs which constitute the MMG. Advanced optimization procedures such as robust optimization (RO) frameworks have been proposed in the literature to handle any uncertainties caused by the stochastic nature of the RES generation, the load demand, and the electricity prices. However, the existing works in the literature do not consider the nonlinear network constraints of individual MGs which might significantly impact the power balance and the power sharing between MGs in MMG systems. This paper proposes a cooperative trading scheme including a two-stage network-constrained robust energy management system to optimize the resource utilization within each MG and the sharing of resources between the constituent MGs of a MMG system. The results clearly highlight the performance of the proposed approach and the impact of including the AC network constraints on the optimal dispatch of the MMG system under varying uncertainties.
URI: https://hdl.handle.net/10356/148382
DOI: 10.1109/CDC42340.2020.9304376
Schools: School of Electrical and Electronic Engineering 
Rights: © 2020 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/CDC42340.2020.9304376
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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