A non-centralized predictive control strategy for wind farm active power control: a wake-based partitioning approach

"Owing to wake effects, the power production of each turbine in a wind farm is highly coupled to the operating conditions of the other turbines. Wind farm control strategies must take into account these couplings and produce individual power commands for each turbine. In this case, centralized...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Siniscalchi-Minna, Sara, Bianchi, Fernando D., Ocampo-Martínez, Carlos, Domínguez-García, José Luis, De Schutter, Bart
Formato: Artículos de Publicaciones Periódicas acceptedVersion
Lenguaje:Inglés
Publicado: info
Materias:
CONTROL PREDICTIVO
ALGORITMOS
ENERGIA EOLICA
Acceso en línea:http://ri.itba.edu.ar/handle/123456789/2237
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-2237
record_format dspace
spelling I32-R138-123456789-22372022-12-07T13:06:35Z A non-centralized predictive control strategy for wind farm active power control: a wake-based partitioning approach Siniscalchi-Minna, Sara Bianchi, Fernando D. Ocampo-Martínez, Carlos Domínguez-García, José Luis De Schutter, Bart CONTROL PREDICTIVO ALGORITMOS ENERGIA EOLICA "Owing to wake effects, the power production of each turbine in a wind farm is highly coupled to the operating conditions of the other turbines. Wind farm control strategies must take into account these couplings and produce individual power commands for each turbine. In this case, centralized control approaches might be prone to failures due to the high computational burden and communication dependency. To overcome this problem, this paper proposes a non-centralized scheme based on splitting the wind farm into almost uncoupled sets of turbines by solving a mixed-integer partitioning problem. In each set of turbines, a model predictive control strategy seeks to optimize the distribution of the power set-points among turbines such that the impact of the power losses due to the wake effect is reduced. Then, a supervisory controller coordinates the generation of each group to satisfy the power demanded by the grid operator. The effectiveness of the proposed control scheme in terms of reduction of computational costs and power regulation is confirmed by simulations for a wind farm of 42 turbines." info:eu-repo/date/embargoEnd/2022-05-01 2020-07-01T19:02:05Z 2020-07-01T19:02:05Z 2020-05 Artículos de Publicaciones Periódicas info:eu-repo/semantics/acceptedVersion 0960-1481 http://ri.itba.edu.ar/handle/123456789/2237 en info:eu-repo/semantics/altIdentifier/doi/10.1016/j.renene.2019.12.139 info:eu-repo/grantAgreement/UE/H2020/EU. Bruselas info:eu-repo/grantAgreement/Marie Sklodowska-Curie/INCITE/675318/SP. Barcelona info:eu-repo/semantics/embargoedAccess application/pdf
institution Instituto Tecnológico de Buenos Aires (ITBA)
institution_str I-32
repository_str R-138
collection Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA)
language Inglés
topic CONTROL PREDICTIVO
ALGORITMOS
ENERGIA EOLICA
spellingShingle CONTROL PREDICTIVO
ALGORITMOS
ENERGIA EOLICA
Siniscalchi-Minna, Sara
Bianchi, Fernando D.
Ocampo-Martínez, Carlos
Domínguez-García, José Luis
De Schutter, Bart
A non-centralized predictive control strategy for wind farm active power control: a wake-based partitioning approach
topic_facet CONTROL PREDICTIVO
ALGORITMOS
ENERGIA EOLICA
description "Owing to wake effects, the power production of each turbine in a wind farm is highly coupled to the operating conditions of the other turbines. Wind farm control strategies must take into account these couplings and produce individual power commands for each turbine. In this case, centralized control approaches might be prone to failures due to the high computational burden and communication dependency. To overcome this problem, this paper proposes a non-centralized scheme based on splitting the wind farm into almost uncoupled sets of turbines by solving a mixed-integer partitioning problem. In each set of turbines, a model predictive control strategy seeks to optimize the distribution of the power set-points among turbines such that the impact of the power losses due to the wake effect is reduced. Then, a supervisory controller coordinates the generation of each group to satisfy the power demanded by the grid operator. The effectiveness of the proposed control scheme in terms of reduction of computational costs and power regulation is confirmed by simulations for a wind farm of 42 turbines."
format Artículos de Publicaciones Periódicas
acceptedVersion
author Siniscalchi-Minna, Sara
Bianchi, Fernando D.
Ocampo-Martínez, Carlos
Domínguez-García, José Luis
De Schutter, Bart
author_facet Siniscalchi-Minna, Sara
Bianchi, Fernando D.
Ocampo-Martínez, Carlos
Domínguez-García, José Luis
De Schutter, Bart
author_sort Siniscalchi-Minna, Sara
title A non-centralized predictive control strategy for wind farm active power control: a wake-based partitioning approach
title_short A non-centralized predictive control strategy for wind farm active power control: a wake-based partitioning approach
title_full A non-centralized predictive control strategy for wind farm active power control: a wake-based partitioning approach
title_fullStr A non-centralized predictive control strategy for wind farm active power control: a wake-based partitioning approach
title_full_unstemmed A non-centralized predictive control strategy for wind farm active power control: a wake-based partitioning approach
title_sort non-centralized predictive control strategy for wind farm active power control: a wake-based partitioning approach
publishDate info
url http://ri.itba.edu.ar/handle/123456789/2237
work_keys_str_mv AT siniscalchiminnasara anoncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
AT bianchifernandod anoncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
AT ocampomartinezcarlos anoncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
AT dominguezgarciajoseluis anoncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
AT deschutterbart anoncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
AT siniscalchiminnasara noncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
AT bianchifernandod noncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
AT ocampomartinezcarlos noncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
AT dominguezgarciajoseluis noncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
AT deschutterbart noncentralizedpredictivecontrolstrategyforwindfarmactivepowercontrolawakebasedpartitioningapproach
_version_ 1765660979452968960

Ejemplares similares