A new rooted tree optimization algorithm for indirect power control of wind turbine based on a doubly-fed induction generator

Benamor, Afaf; Benchouia, Mohamed Toufik; Srairi, K.; Benbouzid, Mohamed

doi:10.1016/j.isatra.2018.11.023

Cited by 34 publications

(27 citation statements)

References 25 publications

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“…Benbouzid et al (2010) [11] presented a control that led to the production of electricity under variable speed for WT systems. Systems have two operating zones that depend on WT tip speed ratio.…”

Section: Literature Reviewmentioning

confidence: 99%

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Rooted Tree Optimization for the Backstepping Power Control of a Doubly Fed Induction Generator Wind Turbine: dSPACE Implementation

et al. 2021

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With the development of wind power generation in recent years, several studies have dealt with the active and reactive power control of wind power systems, along with the quality of energy produced and the connection to distribution networks. In this context, this research proposes a new contribution to the field. The major objective of this work is the development of a nonlinear adaptive backstepping control technique applied to a DFIG based wind system and an optimization technique that uses the rooted tree optimization (RTO) algorithm. The backstepping control strategy is based on the Lyapunov nonlinear technique to guarantee the stability of the system. It is applied to the two converters (i.e., machine and network sides) and subsequently improved with estimators to make the proposed system robust to parametric variation. The RTO technique is based on monitoring the behavior of the underlying foundation of trees in search of underground water in accordance with the level of underground control. The solution proposed for the control is validated using two methods: (1) a simulation on MATLAB/Simulink to test the continuation of the reference (real wind speed) and the robustness of the system and (2) a real-time implementation on a dSPACE-DS1104 board connected to an experimental bench in a laboratory. Simulation and experimental results highlight the validation of the proposed model with better performance compared with other control techniques, such as sliding mode control, direct power control, and field-oriented control.

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Section: Literature Reviewmentioning

confidence: 99%

“…The basic development for trees is related to a very rooted structure. From this point of view, underground root practices are considered cutting edge innovations [11], [25]. This notion implies that the main tree provides various roots to begin the search.…”

Section: Rto Algorithmmentioning

confidence: 99%

Rooted Tree Optimization for the Backstepping Power Control of a Doubly Fed Induction Generator Wind Turbine: dSPACE Implementation

et al. 2021

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“…The results obtained are good but present several problems (chattering phenomenon). [11] presents in his work a control that leads to the production of electricity under variable speed for wind turbine systems. These systems have two operating zones which depend on the wind turbine tip speed ratio.…”

Section: Literature Reviewmentioning

confidence: 99%

“…On the other hand, the control in the grid side ensures the stability of the amplitude voltage of the DC-link and maintains the unit power factor [10][11][12][13][14][15]. To do that, we express the errors , such as: As mentioned before, the derivative of Lyapunov functions (V 1 and V 2 ) must be negative.…”

Section: B Grid Side Converter Controlmentioning

confidence: 99%

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Rooted Tree Optimization for Backstepping Power Control of DFIG Wind Turbine: dSPACE Implementation

Bossoufi¹,

Karim²,

Taoussi³

et al. 2020

Preprint

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This work is devoted to a new contribution to the field of optimization and control of a wind energy conversion system (WECS). A Rooted Tree Optimisation (RTO) will be applied to the non-linear adaptive Backstepping technique to improve its robustness and performance. The non-linear Backstepping control was carried out to control the powers of the doubly-fed induction generator (DFIG) connected to the electrical network by two converters (network side and machine side). Initially, a review of the wind power system was presented. Then, an exhaustive explanation of the Backstepping technique based on the Lyapunov stability and the optimization method was reported. Subsequently, a validation on the Matlab & Simulink environment was carried out to test the performance and robustness of the proposed model. The last part of this work was dedicated to the experiment of the Backstepping adaptive algorithm on a test bench using the dSPACE-DS1104 card, to prove the performance of the system. The results obtained of this work either by follow-up or robustness tests or by experimental validation show a great improvement in terms of performance compared to other control techniques.

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Adaptive FOPI controller based on the fuzzy supervisory for wind power conversion system equipped by a doubly fed induction generator

Kasbi

Rahali

2021

Int Trans Electr Energ Syst

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Summary Wind power systems have non‐linear dynamics and contain many uncertainties such as the parametric uncertainty and the unknown external disturbances. For these reasons, it is a crucial task to design the robust control systems to assure a robust response of wind systems during uncertainties without deteriorating the supplied power quality or stressing the static power converters. This paper designs an adaptive fractional‐order proportional‐integral (FOPI) control system for a wind power conversion system (WPCS) equipped by a doubly fed induction generator (DFIG) in the electric power grid (EPG) connected mode. The designed adaptive control system combines the robust and intelligent nature of the fuzzy supervisory system (FSS) and simple structure of FOPI controller, where the fuzzy rules are utilized to adjust the FOPI controller parameters based on the error and its rate, resulting in an adaptive fuzzy FOPI (AFFOPI) control system, which can keep the control action touch of the standard FOPI controller and, at the same time, provides the robustness during uncertainties without effect on the power quality supplied to the EPG. Pursuant to the vector control technology of the DFIG, the designed adaptive fuzzy FOPI controllers are applied in both the external loop of power control and in the internal loop of rotor current control, simultaneously. The feasibility of the presented adaptive FOPI control is validated through the numerical results obtained, under different running conditions, using the Matlab/Simulink software.

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A new rooted tree optimization algorithm for indirect power control of wind turbine based on a doubly-fed induction generator

Cited by 34 publications

References 25 publications

Rooted Tree Optimization for the Backstepping Power Control of a Doubly Fed Induction Generator Wind Turbine: dSPACE Implementation

Rooted Tree Optimization for the Backstepping Power Control of a Doubly Fed Induction Generator Wind Turbine: dSPACE Implementation

Rooted Tree Optimization for Backstepping Power Control of DFIG Wind Turbine: dSPACE Implementation

Adaptive FOPI controller based on the fuzzy supervisory for wind power conversion system equipped by a doubly fed induction generator

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