A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy Systems

In this paper, we propose a distributed model predictive control (MPC) scheme for economic dispatch of energy systems with a large number of active components. The scheme uses a distributed optimization algorithm that works over random communication networks and asynchronous updates, implying the re...

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Detalles Bibliográficos
Autores: Ananduta, Wicak, Ocampo-Martínez, Carlos, Nedić, Angelia
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2021
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/261090
Acceso en línea:http://hdl.handle.net/10261/261090
Access Level:acceso abierto
Palabra clave:Economic dispatch
Multi-agent optimization
Model predictive control
Stochastic time-varying network
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spelling A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy SystemsAnanduta, WicakOcampo-Martínez, CarlosNedić, AngeliaEconomic dispatchMulti-agent optimizationModel predictive controlStochastic time-varying networkIn this paper, we propose a distributed model predictive control (MPC) scheme for economic dispatch of energy systems with a large number of active components. The scheme uses a distributed optimization algorithm that works over random communication networks and asynchronous updates, implying the resiliency of the proposed scheme with respect to communication problems, such as link failures, data packet drops, and delays. The distributed optimization algorithm is based on the augmented Lagrangian approach, where the dual of the considered convex economic dispatch problem is solved. Furthermore, in order to improve the convergence speed of the algorithm, we adapt Nesterov's accelerated gradient method and apply the warm start method to initialize the variables. We show through numerical simulations of a well-known case study the performance of the proposed scheme.Institute of Electrical and Electronics EngineersConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2022202220212022info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/261090reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttp://dx.doi.org/10.1109/TSTE.2021.3073510Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2610902026-05-22T06:33:51Z
dc.title.none.fl_str_mv A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy Systems
title A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy Systems
spellingShingle A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy Systems
Ananduta, Wicak
Economic dispatch
Multi-agent optimization
Model predictive control
Stochastic time-varying network
title_short A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy Systems
title_full A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy Systems
title_fullStr A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy Systems
title_full_unstemmed A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy Systems
title_sort A Distributed Augmented Lagrangian Method over Stochastic Networks for Economic Dispatch of Large-Scale Energy Systems
dc.creator.none.fl_str_mv Ananduta, Wicak
Ocampo-Martínez, Carlos
Nedić, Angelia
author Ananduta, Wicak
author_facet Ananduta, Wicak
Ocampo-Martínez, Carlos
Nedić, Angelia
author_role author
author2 Ocampo-Martínez, Carlos
Nedić, Angelia
author2_role author
author
dc.contributor.none.fl_str_mv Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Economic dispatch
Multi-agent optimization
Model predictive control
Stochastic time-varying network
topic Economic dispatch
Multi-agent optimization
Model predictive control
Stochastic time-varying network
description In this paper, we propose a distributed model predictive control (MPC) scheme for economic dispatch of energy systems with a large number of active components. The scheme uses a distributed optimization algorithm that works over random communication networks and asynchronous updates, implying the resiliency of the proposed scheme with respect to communication problems, such as link failures, data packet drops, and delays. The distributed optimization algorithm is based on the augmented Lagrangian approach, where the dual of the considered convex economic dispatch problem is solved. Furthermore, in order to improve the convergence speed of the algorithm, we adapt Nesterov's accelerated gradient method and apply the warm start method to initialize the variables. We show through numerical simulations of a well-known case study the performance of the proposed scheme.
publishDate 2021
dc.date.none.fl_str_mv 2021
2022
2022
2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/261090
url http://hdl.handle.net/10261/261090
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv http://dx.doi.org/10.1109/TSTE.2021.3073510
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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