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Article: Incorporating Wind Energy in Power System Restoration Planning
Title | Incorporating Wind Energy in Power System Restoration Planning |
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Authors | |
Keywords | Integer L-shaped algorithm mixed-integer linear programming power system restoration stochastic optimization wind uncertainty |
Issue Date | 2019 |
Publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165411 |
Citation | IEEE Transactions on Smart Grid, 2019, v. 10 n. 1, p. 16-28 How to Cite? |
Abstract | Wind energy is rapidly growing. While wind brings us clean and inexpensive energy, its inherent variability and uncertainty present challenges for the power grid. In particular, employing wind energy for power system restoration is very challenging. A fast and reliable restoration plays a vital role to achieve the self-healing power grid. This paper develops a novel offline restoration planning tool for harnessing wind energy to enhance grid resilience. The wind-for-restoration problem is formulated as a stochastic mixed-integer linear programming problem with generated wind energy scenarios. The problem is then decomposed into two stages and solved with the integer L-shaped algorithm. Numerical experiments have been conducted through different case studies using the modified IEEE 57-bus system. The developed tool can provide the scheduled wind power at each restoration time. The impact of wind energy is investigated from the aspects of location and inertia capability, as well as wind penetration, fluctuation, and uncertainty. Moreover, a dynamic response validation tool is developed to validate the results of optimization problem in a dynamic simulation software. Simulation results demonstrate that the optimal wind harnessing strategy can help improve system restoration process and enhance system resilience. © 2010-2012 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/274996 |
ISSN | 2021 Impact Factor: 10.275 2020 SCImago Journal Rankings: 3.571 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Golshani, A | - |
dc.contributor.author | Sun, W | - |
dc.contributor.author | Zhou, Q | - |
dc.contributor.author | Zheng, QP | - |
dc.contributor.author | Hou, Y | - |
dc.date.accessioned | 2019-09-10T02:33:17Z | - |
dc.date.available | 2019-09-10T02:33:17Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | IEEE Transactions on Smart Grid, 2019, v. 10 n. 1, p. 16-28 | - |
dc.identifier.issn | 1949-3053 | - |
dc.identifier.uri | http://hdl.handle.net/10722/274996 | - |
dc.description.abstract | Wind energy is rapidly growing. While wind brings us clean and inexpensive energy, its inherent variability and uncertainty present challenges for the power grid. In particular, employing wind energy for power system restoration is very challenging. A fast and reliable restoration plays a vital role to achieve the self-healing power grid. This paper develops a novel offline restoration planning tool for harnessing wind energy to enhance grid resilience. The wind-for-restoration problem is formulated as a stochastic mixed-integer linear programming problem with generated wind energy scenarios. The problem is then decomposed into two stages and solved with the integer L-shaped algorithm. Numerical experiments have been conducted through different case studies using the modified IEEE 57-bus system. The developed tool can provide the scheduled wind power at each restoration time. The impact of wind energy is investigated from the aspects of location and inertia capability, as well as wind penetration, fluctuation, and uncertainty. Moreover, a dynamic response validation tool is developed to validate the results of optimization problem in a dynamic simulation software. Simulation results demonstrate that the optimal wind harnessing strategy can help improve system restoration process and enhance system resilience. © 2010-2012 IEEE. | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165411 | - |
dc.relation.ispartof | IEEE Transactions on Smart Grid | - |
dc.rights | IEEE Transactions on Smart Grid. Copyright © Institute of Electrical and Electronics Engineers. | - |
dc.rights | ©20xx 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. | - |
dc.subject | Integer L-shaped algorithm | - |
dc.subject | mixed-integer linear programming | - |
dc.subject | power system restoration | - |
dc.subject | stochastic optimization | - |
dc.subject | wind uncertainty | - |
dc.title | Incorporating Wind Energy in Power System Restoration Planning | - |
dc.type | Article | - |
dc.identifier.email | Hou, Y: yhhou@hku.hk | - |
dc.identifier.authority | Hou, Y=rp00069 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TSG.2017.2729592 | - |
dc.identifier.scopus | eid_2-s2.0-85028843770 | - |
dc.identifier.hkuros | 302649 | - |
dc.identifier.volume | 10 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 16 | - |
dc.identifier.epage | 28 | - |
dc.identifier.isi | WOS:000455180900002 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1949-3053 | - |