Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control
This paper introduces a sliding-mode-based extremum-seeking algorithm aimed at generating optimal set-points of wind turbines in wind farms. A distributed extremum-seeking control is directed to fully utilize the captured wind energy by taking into consideration the wake and aerodynamic properties b...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/4/828 |
| _version_ | 1797414497951940608 |
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| author | Yasser Bin Salamah Umit Ozguner |
| author_facet | Yasser Bin Salamah Umit Ozguner |
| author_sort | Yasser Bin Salamah |
| collection | DOAJ |
| description | This paper introduces a sliding-mode-based extremum-seeking algorithm aimed at generating optimal set-points of wind turbines in wind farms. A distributed extremum-seeking control is directed to fully utilize the captured wind energy by taking into consideration the wake and aerodynamic properties between wind turbines. The proposed approach is a model-free algorithm. Namely, it is independent of the model selection of the wake interaction between the wind turbines. The proposed distributed scheme consists of two parts. A dynamic consensus algorithm and an extremum-seeking controller based on sliding-mode theory. The distributed consensus algorithm is exploited to estimate the value of the total power produced by a wind farm. Subsequently, sliding-mode extremum-seeking controllers are intended to cooperatively produce optimal set-points for wind turbines within the farm. Scheme performance is tested via extensive simulations under both steady and varying wind speed and directions. The presented distributed scheme is compared with a centralized approach, in which the problem can be seen as a multivariable optimization. The results show that the employed scheme is able to successfully maximize power production in wind farms. |
| first_indexed | 2024-03-09T05:34:08Z |
| format | Article |
| id | doaj.art-0d431392733046b284cfd7bacaf6ca1e |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T05:34:08Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-0d431392733046b284cfd7bacaf6ca1e2023-12-03T12:30:08ZengMDPI AGEnergies1996-10732021-02-0114482810.3390/en14040828Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode ControlYasser Bin Salamah0Umit Ozguner1Department of Electrical Engineering, King Saud Univeristy, Riyadh 11451, Saudi ArabiaDepartment of Electrical & Computer Engineering, Ohio State University, Columbus, OH 43210, USAThis paper introduces a sliding-mode-based extremum-seeking algorithm aimed at generating optimal set-points of wind turbines in wind farms. A distributed extremum-seeking control is directed to fully utilize the captured wind energy by taking into consideration the wake and aerodynamic properties between wind turbines. The proposed approach is a model-free algorithm. Namely, it is independent of the model selection of the wake interaction between the wind turbines. The proposed distributed scheme consists of two parts. A dynamic consensus algorithm and an extremum-seeking controller based on sliding-mode theory. The distributed consensus algorithm is exploited to estimate the value of the total power produced by a wind farm. Subsequently, sliding-mode extremum-seeking controllers are intended to cooperatively produce optimal set-points for wind turbines within the farm. Scheme performance is tested via extensive simulations under both steady and varying wind speed and directions. The presented distributed scheme is compared with a centralized approach, in which the problem can be seen as a multivariable optimization. The results show that the employed scheme is able to successfully maximize power production in wind farms.https://www.mdpi.com/1996-1073/14/4/828extremum seekingnetworked control systemsrenewable energy sourcessliding mode control |
| spellingShingle | Yasser Bin Salamah Umit Ozguner Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control Energies extremum seeking networked control systems renewable energy sources sliding mode control |
| title | Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control |
| title_full | Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control |
| title_fullStr | Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control |
| title_full_unstemmed | Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control |
| title_short | Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control |
| title_sort | distributed extremum seeking for wind farm power maximization using sliding mode control |
| topic | extremum seeking networked control systems renewable energy sources sliding mode control |
| url | https://www.mdpi.com/1996-1073/14/4/828 |
| work_keys_str_mv | AT yasserbinsalamah distributedextremumseekingforwindfarmpowermaximizationusingslidingmodecontrol AT umitozguner distributedextremumseekingforwindfarmpowermaximizationusingslidingmodecontrol |