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Article: MDP-Based Distribution Network Reconfiguration With Renewable Distributed Generation: Approximate Dynamic Programming Approach
Title | MDP-Based Distribution Network Reconfiguration With Renewable Distributed Generation: Approximate Dynamic Programming Approach |
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Authors | |
Keywords | Approximate dynamic programming distributed generation distribution systems Markov decision processes reconfiguration |
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. 4, p. 3620-3631 How to Cite? |
Abstract | Growing penetration of renewable distributed generation, a major concern nowadays, has played a critical role in distribution system operation. This paper develops a state-based sequential network reconfiguration strategy by using a Markov decision process (MDP) model with the objective of minimizing renewable distributed generation curtailment and load shedding under operational constraints. Available power outputs of distributed generators and the system topology in each decision time are represented as Markov states, which are driven to other Markov states in next decision time in consideration of uncertainties of renewable distributed generation. For each Markov state in each decision time, a recursive optimization model with a current cost and a future cost is developed to make state-based actions, including system reconfiguration, load shedding, and distributed generation curtailment. To address the curse of dimensionality caused by enormous states and actions in the proposed model, an approximate dynamic programming (ADP) approach, including post-decision states and forward dynamic algorithm, 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/10722/289705 |
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 | Lei, S | - |
dc.contributor.author | Ju, P | - |
dc.contributor.author | Chen, C | - |
dc.contributor.author | Peng, C | - |
dc.contributor.author | Hou, Y | - |
dc.date.accessioned | 2020-10-22T08:16:16Z | - |
dc.date.available | 2020-10-22T08:16:16Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | IEEE Transactions on Smart Grid, 2020, v. 11 n. 4, p. 3620-3631 | - |
dc.identifier.issn | 1949-3053 | - |
dc.identifier.uri | http://hdl.handle.net/10722/289705 | - |
dc.description.abstract | Growing penetration of renewable distributed generation, a major concern nowadays, has played a critical role in distribution system operation. This paper develops a state-based sequential network reconfiguration strategy by using a Markov decision process (MDP) model with the objective of minimizing renewable distributed generation curtailment and load shedding under operational constraints. Available power outputs of distributed generators and the system topology in each decision time are represented as Markov states, which are driven to other Markov states in next decision time in consideration of uncertainties of renewable distributed generation. For each Markov state in each decision time, a recursive optimization model with a current cost and a future cost is developed to make state-based actions, including system reconfiguration, load shedding, and distributed generation curtailment. To address the curse of dimensionality caused by enormous states and actions in the proposed model, an approximate dynamic programming (ADP) approach, including post-decision states and forward dynamic algorithm, 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 | Approximate dynamic programming | - |
dc.subject | distributed generation | - |
dc.subject | distribution systems | - |
dc.subject | Markov decision processes | - |
dc.subject | reconfiguration | - |
dc.title | MDP-Based Distribution Network Reconfiguration With Renewable Distributed Generation: 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.2019.2963696 | - |
dc.identifier.scopus | eid_2-s2.0-85087429153 | - |
dc.identifier.hkuros | 316774 | - |
dc.identifier.volume | 11 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | 3620 | - |
dc.identifier.epage | 3631 | - |
dc.identifier.isi | WOS:000542571700072 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1949-3053 | - |