Motivated by the increasing concerns over environmental challenges such as global warming and exhaustion of fossil-fuel reserves, the renewable energy industry has become the most sought-after source of electrical energy production worldwide. In this context, wind energy conversion systems (WECS) are one of the most dominant and fastest-growing technologies, playing an increasingly vital role in renewable power generation. To meet this growing demand and mitigate the vulnerability of WECS to various sets of internal/external faults, the cost-effectiveness and efficient power production of WECS must be ensured, which highlights the critical role of the control system. This topic has been intensively studied in the literature, and many control approaches have been developed to deal with the simultaneous enhancement of efficiency and reliability of WECS. However, sliding mode control (SMC) has proved its reliable and superior performance among most control strategies due to its inherent robustness to parametric uncertainties and disturbances and ease of design and implementation. Accordingly, this paper provides a comprehensive survey of existing literature on the application of SMC and its emerging modifications to address different control design problems for WECS. 

Sliding mode control of wind energy conversion systems: Trends and applications

https://www.econstor.eu/bitstream/10419/243633/1/1671087801.pdf

Optimization and control of water pumping PV systems using fuzzy logic controller

This paper presents a new contribution in the field of the optimization of the techniques of control of the wind systems and the improvement of the quality of energy produced in the grid. The Sliding Mode control technique gives quite interesting results, but its major drawback lies in the phenomenon of chattering (oscillations), which reduces the system's precision. We propose in this work a solution to cancel this chattering phenomenon by the implication of the adaptive Backstepping technique to control the powers of the double-fed asynchronous generator (DFIG) connected to the electrical network by two converters (network side and side machine) in the nominal part of the sliding mode model. This hybrid technique will correct errors of precision and stability and the performance of the wind system obtained in terms of efficiency, active and reactive power is significant. First, a review of the wind system was presented. Then, an exhaustive explanation of the Backstepping technique based on the Lyapunov stability and optimization method has been reported. Subsequently, a validation on the Matlab & Simulink environment was carried out to test the performance and robustness of the proposed model. The results obtained from this work, either by follow-up or robustness tests, show a significant performance improvement compared to other control techniques. 

/pdf/robust-sliding-backstepping-mode-control-of-a-wind-system-2cg4evvb.pdf

Robust sliding-Backstepping mode control of a wind system based on the DFIG generator

/pdf/robust-sliding-backstepping-mode-control-of-a-wind-system-1x18s4z0.pdf

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.

/pdf/rooted-tree-optimization-for-the-backstepping-power-control-1jsbdjjsau.pdf

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

A novel rooted tree optimization apply in the high order sliding mode control using super-twisting algorithm based on DTC scheme for DFIG

A new control strategy based on the root tree optimization (RTO) is presented in order to reduce the chattering phenomena in active and reactive powers, and to minimize the harmonic currents which appear mostly at the level of the rotor side converter (RSC), in a doubly-fed induction generator (DFIG). The root tree optimization is used to adjust the parameters (Kp,Ki) of PI controller (RTO-PI). Simulation results are presented to demonstrate the effectiveness of the new proposed technique. Besides, the system associated with this metaheuristic algorithm can effectively give better dynamic and steady performance. The results with the RTO-PI controller show more performances than the results compared with the classical PI.

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

To well manage the quality of the injected electrical power into the grid from a variable speed wind turbine (VSWT), direct power control (DPC) scheme using second order sliding mode control (SOSMC) based on super-twisting algorithm (STA) approach is proposed. Meanwhile, for reaching the adequate gains of STA, an appropriate optimizer should be implemented. Therefore, shuffled complex evolution (SCE) algorithm-based parameter identification is suggested. To verify the effectiveness of the proposed SCE based controller, several well-known algorithms have been tested under various operating conditions namely: particle swarm optimizer (PSO), artificial bee colony optimizer (ABCO), ant colony optimization (ACO), rooted tree optimizer (RTO) and gray wolf optimizer (GWO). The results confirm the superiority of the proposed SCE algorithm among the competing algorithms and classic SMC regarding the active power steady-state error (0.7233%), undershoot percentage (0.1333%), settling time (0.6810 × 10-3 s), rise time (1.7515 × 10-4 s), peak value (7.0521 × 103 W), overall efficiency (99.2800%), and total harmonic distortion (0.7900%). The proposed SCE based controller allows getting important performances under various operating condition of wind speed and load variations with interesting electrical network stability. 

Efficient PMSG wind turbine with energy storage system control based shuffled complex evolution optimizer.

The integration of wind turbines (WTs) in variable speed drive systems belongs to the main factors causing low stability in electrical networks. Therefore, in order to avoid this issue, WTs hybridization with a storage system is a mandatory. This paper investigates WT system operating at variable speed. The system contains of a permanent magnet synchronous generator (PMSG) supported by a battery storage system (BSS). To enhance the quality of active and reactive power injected into the network, direct power control (DPC) scheme utilizing space-vector modulation (SVM) technique based on proportional-integral (PI) control is proposed. Meanwhile, to improve the rendition of this method (DPC-SVM-PI), the rooted tree optimization technique (RTO) algorithm-based controller parameter identification is used to achieve PI optimal gains. To compare the performance of RTO-based controllers, they were implemented and tested along with some other popular controllers under different working conditions. The obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion (THD), overshoot percentage, settling time, rise time, average active power value, overall efficiency, and active power steady-state error. 

/pdf/rooted-tree-optimization-for-wind-turbine-optimum-control-1qejqbil.pdf

Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

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Papers

A novel rooted tree optimization apply in the high order sliding mode control using super-twisting algorithm based on DTC scheme for DFIG

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

Efficient PMSG wind turbine with energy storage system control based shuffled complex evolution optimizer.

Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System