Xu, X, Li, K orcid.org/0000-0001-6657-0522, Liu, Y et al. (1 more author) (2016) Integrated optimal power flow for distribution networks in local and urban scales. In: Proceedings of the 2016 UKACC 11th International Conference on Control (CONTROL). 2016 UKACC 11th International Conference on Control (CONTROL), 31 Aug - 02 Sep 2016, Belfast, UK. IEEE ISBN 978-1-4673-9891-6
Abstract
This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | distribution network; spatial scales; natural gas network; integrated optimal power flow; energy hub |
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 14:53 |
Last Modified: | 05 Nov 2019 14:53 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/control.2016.7737523 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:153033 |