Sparsity-promoting distributed charging control for plug-in electric vehicles over distribution networks
Uncoordinated charging of plug-in electric vehicles brings a new challenge on the operation of a power system as it causes power flow fluctuations and even unacceptable load peaks. To ensure the stability of power network, plug-in charging needs to be scheduled against the base load properly. In thi...
| Main Authors: | , , , , , |
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| Format: | Journal Article |
| Published: |
Elsevier
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/67079 |
| _version_ | 1848761469482565632 |
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| author | Li, J. Li, C. Wu, Z. Wang, Xiangyu Teo, Kok Lay Wu, Changzhi |
| author_facet | Li, J. Li, C. Wu, Z. Wang, Xiangyu Teo, Kok Lay Wu, Changzhi |
| author_sort | Li, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Uncoordinated charging of plug-in electric vehicles brings a new challenge on the operation of a power system as it causes power flow fluctuations and even unacceptable load peaks. To ensure the stability of power network, plug-in charging needs to be scheduled against the base load properly. In this paper, we propose a sparsity-promoting charging control model to address this issue. In the model, the satisfaction of customers is improved through sparsity-promoting charging where the numbers of charging time slots are optimized. Dynamic feeder overload constraints are imposed in the model to avoid any unacceptable load peaks, and thus ensure the network stability. Then, a distributed solution strategy is de veloped to solve the problem based on the alternating direction method of multipliers (ADMM) since most of power networks are managed typically in a distributed manner. During solving process, Lagrangian duality is used to transform the original problem into an equivalent dual problem, which can be decomposed into a set of homogeneous small-scaled sub-problems. Particularly, each sub-problem either has a closed-form solution or can be solved locally by an accelerated dual gradient method. The global convergence of the proposed algorithm is also established. Finally, numerical simulations are presented to illustrate our proposed method. In contrast to traditional charging models, our sparsity-promoting charging model not only ensures the stability of power network, but also improves the satisfaction of customers. |
| first_indexed | 2025-11-14T10:32:10Z |
| format | Journal Article |
| id | curtin-20.500.11937-67079 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:32:10Z |
| publishDate | 2018 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-670792018-09-19T01:32:04Z Sparsity-promoting distributed charging control for plug-in electric vehicles over distribution networks Li, J. Li, C. Wu, Z. Wang, Xiangyu Teo, Kok Lay Wu, Changzhi Uncoordinated charging of plug-in electric vehicles brings a new challenge on the operation of a power system as it causes power flow fluctuations and even unacceptable load peaks. To ensure the stability of power network, plug-in charging needs to be scheduled against the base load properly. In this paper, we propose a sparsity-promoting charging control model to address this issue. In the model, the satisfaction of customers is improved through sparsity-promoting charging where the numbers of charging time slots are optimized. Dynamic feeder overload constraints are imposed in the model to avoid any unacceptable load peaks, and thus ensure the network stability. Then, a distributed solution strategy is de veloped to solve the problem based on the alternating direction method of multipliers (ADMM) since most of power networks are managed typically in a distributed manner. During solving process, Lagrangian duality is used to transform the original problem into an equivalent dual problem, which can be decomposed into a set of homogeneous small-scaled sub-problems. Particularly, each sub-problem either has a closed-form solution or can be solved locally by an accelerated dual gradient method. The global convergence of the proposed algorithm is also established. Finally, numerical simulations are presented to illustrate our proposed method. In contrast to traditional charging models, our sparsity-promoting charging model not only ensures the stability of power network, but also improves the satisfaction of customers. 2018 Journal Article http://hdl.handle.net/20.500.11937/67079 10.1016/j.apm.2017.10.034 Elsevier restricted |
| spellingShingle | Li, J. Li, C. Wu, Z. Wang, Xiangyu Teo, Kok Lay Wu, Changzhi Sparsity-promoting distributed charging control for plug-in electric vehicles over distribution networks |
| title | Sparsity-promoting distributed charging control for plug-in electric vehicles over distribution networks |
| title_full | Sparsity-promoting distributed charging control for plug-in electric vehicles over distribution networks |
| title_fullStr | Sparsity-promoting distributed charging control for plug-in electric vehicles over distribution networks |
| title_full_unstemmed | Sparsity-promoting distributed charging control for plug-in electric vehicles over distribution networks |
| title_short | Sparsity-promoting distributed charging control for plug-in electric vehicles over distribution networks |
| title_sort | sparsity-promoting distributed charging control for plug-in electric vehicles over distribution networks |
| url | http://hdl.handle.net/20.500.11937/67079 |