Resilient distributed model predictive control for energy management of interconnected microgrids

Distributed energy management of interconnected microgrids that is based on Model Predictive Control (MPC) relies on the cooperation of all agents (microgrids). This paper discusses the case in which some of the agents might perform one type of adversarial actions (attacks) and they do not comply wi...

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Autores: Ananduta, Wayan Wicak, Maestre Torreblanca, José María, Ocampo-Martínez, Carlos|||0000-0001-9251-6044, Ishii, Hideaki
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/183813
Acceso en línea:https://hdl.handle.net/2117/183813
https://dx.doi.org/10.1002/oca.2534
Access Level:acceso abierto
Palabra clave:Distributed MPC
Economic dispatch
Distributed optimization
Resilient algorithm
Microgrids
Classificació INSPEC::Control theory
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
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spelling Resilient distributed model predictive control for energy management of interconnected microgridsAnanduta, Wayan WicakMaestre Torreblanca, José MaríaOcampo-Martínez, Carlos|||0000-0001-9251-6044Ishii, HideakiDistributed MPCEconomic dispatchDistributed optimizationResilient algorithmMicrogridsClassificació INSPEC::Control theoryÀrees temàtiques de la UPC::Informàtica::Automàtica i controlDistributed energy management of interconnected microgrids that is based on Model Predictive Control (MPC) relies on the cooperation of all agents (microgrids). This paper discusses the case in which some of the agents might perform one type of adversarial actions (attacks) and they do not comply with the decisions computed by performing a distributed MPC algorithm. In this regard, these agents could obtain a better performance at the cost of degrading the performance of the network as a whole. A resilient distributed method that can deal with such issues is proposed in this paper. The method consists of two parts. The first part is to ensure that the decisions obtained from the algorithm are robustly feasible against most of the attacks with high confidence. In this part, we formulate the economic dispatch problem, taking into account the attacks as a chance-constrained problem and employ a two-step randomization-based approach to obtain a feasible solution with a predefined level of confidence. The second part consists in the identification and mitigation of the adversarial agents, which utilizes hypothesis testing with Bayesian inference and requires each agent to solve a mixed-integer problem to decide the connections with its neighbors. In addition, an analysis of the decisions computed using the stochastic approach and the outcome of the identification and mitigation method is provided. The performance of the proposed approach is also shown through numerical simulations.Funding information Marie Skłodowska-Curie, Grant/Award Number: 675318; Maria de Maeztu Seal of Excellence to IRI, Grant/Award Number: MDM-2016-0656; Spanish MINECO project, Grant/Award Number: DPI2017-86918-R; Japanese Society for the Promotion of Science Scholarship, Grant/Award Number: PE16048; JST CREST, Grant/Award Number: JPMJCR15K3 and JPMJCR15Peer Reviewed20192019-01-0120202020-04-17journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/183813https://dx.doi.org/10.1002/oca.2534reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 675318 Innovative controls for renewable sources Integration into smart energy systemsopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1838132026-05-27T15:37:01Z
dc.title.none.fl_str_mv Resilient distributed model predictive control for energy management of interconnected microgrids
title Resilient distributed model predictive control for energy management of interconnected microgrids
spellingShingle Resilient distributed model predictive control for energy management of interconnected microgrids
Ananduta, Wayan Wicak
Distributed MPC
Economic dispatch
Distributed optimization
Resilient algorithm
Microgrids
Classificació INSPEC::Control theory
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
title_short Resilient distributed model predictive control for energy management of interconnected microgrids
title_full Resilient distributed model predictive control for energy management of interconnected microgrids
title_fullStr Resilient distributed model predictive control for energy management of interconnected microgrids
title_full_unstemmed Resilient distributed model predictive control for energy management of interconnected microgrids
title_sort Resilient distributed model predictive control for energy management of interconnected microgrids
dc.creator.none.fl_str_mv Ananduta, Wayan Wicak
Maestre Torreblanca, José María
Ocampo-Martínez, Carlos|||0000-0001-9251-6044
Ishii, Hideaki
author Ananduta, Wayan Wicak
author_facet Ananduta, Wayan Wicak
Maestre Torreblanca, José María
Ocampo-Martínez, Carlos|||0000-0001-9251-6044
Ishii, Hideaki
author_role author
author2 Maestre Torreblanca, José María
Ocampo-Martínez, Carlos|||0000-0001-9251-6044
Ishii, Hideaki
author2_role author
author
author
dc.subject.none.fl_str_mv Distributed MPC
Economic dispatch
Distributed optimization
Resilient algorithm
Microgrids
Classificació INSPEC::Control theory
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
topic Distributed MPC
Economic dispatch
Distributed optimization
Resilient algorithm
Microgrids
Classificació INSPEC::Control theory
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
description Distributed energy management of interconnected microgrids that is based on Model Predictive Control (MPC) relies on the cooperation of all agents (microgrids). This paper discusses the case in which some of the agents might perform one type of adversarial actions (attacks) and they do not comply with the decisions computed by performing a distributed MPC algorithm. In this regard, these agents could obtain a better performance at the cost of degrading the performance of the network as a whole. A resilient distributed method that can deal with such issues is proposed in this paper. The method consists of two parts. The first part is to ensure that the decisions obtained from the algorithm are robustly feasible against most of the attacks with high confidence. In this part, we formulate the economic dispatch problem, taking into account the attacks as a chance-constrained problem and employ a two-step randomization-based approach to obtain a feasible solution with a predefined level of confidence. The second part consists in the identification and mitigation of the adversarial agents, which utilizes hypothesis testing with Bayesian inference and requires each agent to solve a mixed-integer problem to decide the connections with its neighbors. In addition, an analysis of the decisions computed using the stochastic approach and the outcome of the identification and mitigation method is provided. The performance of the proposed approach is also shown through numerical simulations.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-01-01
2020
2020-04-17
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/183813
https://dx.doi.org/10.1002/oca.2534
url https://hdl.handle.net/2117/183813
https://dx.doi.org/10.1002/oca.2534
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 675318 Innovative controls for renewable sources Integration into smart energy systems
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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