Yang, Z, Li, K orcid.org/0000-0001-6657-0522 and Xu, X (2016) A hybrid meta-heuristic method for unit commitment considering flexible charging and discharging of plug-in electric vehicles. In: Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC). 2016 IEEE Congress on Evolutionary Computation (CEC), 24-29 Jul 2016, Vancouver, BC, Canada. IEEE , pp. 2014-2020. ISBN 978-1-5090-0623-6
Abstract
Unit commitment is a key issue in power system operation and has long been an intractable problem due to its complex mix-integer nonlinear formulation. The original unit commitment problem aims to minimize the fossil fuel cost by determining the on/off status of power units and power contribution of each online unit at the same time. However, the uncoordinated large charging power necessity of plug-in electric vehicles brings unprecedented challenges to the power system operators and further complicates the unit commitment problem. To seamless integrate the plug-in electric vehicles into the unit commitment, a new binary/real-value hybrid meta-heuristic algorithm framework is proposed in this paper, simultaneously determining the binary status and power output of units as well as the power delivered to/feedback from flexible charging and discharging of plug-in electric vehicles. A batch of binary particle swarm optimisation variants with different transfer functions are implemented and compared in solving the unit commitment problem with and without plug-in electric vehicles. Numerical studies illustrate the effectiveness of the proposed intelligent algorithm and the impact of different transfer functions is evaluated.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | unit commitment; plug-in electric vehicles; binary; real-valued; transfer function |
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: | 05 Nov 2019 16:16 |
Last Modified: | 05 Nov 2019 16:16 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/cec.2016.7744035 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:153024 |