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Article: Markov Decision Process-Based Resilience Enhancement for Distribution Systems: An Approximate Dynamic Programming Approach
Title | Markov Decision Process-Based Resilience Enhancement for Distribution Systems: An Approximate Dynamic Programming Approach |
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Authors | |
Keywords | Markov processes Load modeling Meteorology Topology Power systems |
Issue Date | 2020 |
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, 2020, v. 11 n. 3, p. 2498-2510 How to Cite? |
Abstract | Because failures in distribution systems caused by extreme weather events directly result in consumers' outages, this paper proposes a state-based decision-making model with the objective of mitigating loss of load to improve the distribution system resilience throughout the unfolding events. The system topologies including on/off states of feeder lines are modeled as Markov states, and the probabilities from one Markov state to another Markov state throughout the unfolding events are determined by the component failure caused by the unfolding events. A recursive optimization model based on Markov decision processes (MDP) is developed to make state-based actions, i.e., system reconfiguration, at each decision time. To overcome the curse of dimensionality caused by enormous states and actions, an approximate dynamic programming (ADP) approach based on post-decision states and iteration is used to solve the proposed MDP-based model. IEEE 33-bus system and IEEE 123-bus system are used to validate the proposed model. |
Persistent Identifier | http://hdl.handle.net/10722/282908 |
ISSN | 2023 Impact Factor: 8.6 2023 SCImago Journal Rankings: 4.863 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Wang, C | - |
dc.contributor.author | Ju, P | - |
dc.contributor.author | Lei, S | - |
dc.contributor.author | Wang, Z | - |
dc.contributor.author | Wu, F | - |
dc.contributor.author | Hou, Y | - |
dc.date.accessioned | 2020-06-05T06:22:57Z | - |
dc.date.available | 2020-06-05T06:22:57Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | IEEE Transactions on Smart Grid, 2020, v. 11 n. 3, p. 2498-2510 | - |
dc.identifier.issn | 1949-3053 | - |
dc.identifier.uri | http://hdl.handle.net/10722/282908 | - |
dc.description.abstract | Because failures in distribution systems caused by extreme weather events directly result in consumers' outages, this paper proposes a state-based decision-making model with the objective of mitigating loss of load to improve the distribution system resilience throughout the unfolding events. The system topologies including on/off states of feeder lines are modeled as Markov states, and the probabilities from one Markov state to another Markov state throughout the unfolding events are determined by the component failure caused by the unfolding events. A recursive optimization model based on Markov decision processes (MDP) is developed to make state-based actions, i.e., system reconfiguration, at each decision time. To overcome the curse of dimensionality caused by enormous states and actions, an approximate dynamic programming (ADP) approach based on post-decision states and iteration is used to solve the proposed MDP-based model. IEEE 33-bus system and IEEE 123-bus system are used to validate the proposed model. | - |
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 | Markov processes | - |
dc.subject | Load modeling | - |
dc.subject | Meteorology | - |
dc.subject | Topology | - |
dc.subject | Power systems | - |
dc.title | Markov Decision Process-Based Resilience Enhancement for Distribution Systems: An Approximate Dynamic Programming Approach | - |
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.2019.2956740 | - |
dc.identifier.scopus | eid_2-s2.0-85083957381 | - |
dc.identifier.hkuros | 310273 | - |
dc.identifier.hkuros | 316714 | - |
dc.identifier.volume | 11 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 2498 | - |
dc.identifier.epage | 2510 | - |
dc.identifier.isi | WOS:000530243600058 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1949-3053 | - |