Xu, X, Li, K orcid.org/0000-0001-6657-0522, Jia, H et al. (3 more authors) (2018) Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines. IEEE Transactions on Smart Grid, 9 (2). pp. 1387-1396. ISSN 1949-3053
Abstract
Microturbines (MTs) are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes, which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of MTs. Considering the time-scale difference of various dynamic processes occurring within MTs, the electromechanical subsystem is treated as a fast quasi-linear process, while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 MT show that the proposed modeling method can well capture the system dynamics, and produce a good prediction of the coupled thermal and electric outputs in various operating modes.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. This is an author produced version of a paper published in IEEE Transactions on Smart Grid. 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. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Microturbine; combined heat and power; dynamic behavior; modeling; system identification |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Jun 2018 09:18 |
Last Modified: | 06 Mar 2019 14:14 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/TSG.2016.2590022 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:132434 |