Second-order sliding mode voltage-regulator for improving MPPT efficiency of PMSG-based WECS

Dursun, Emre Hasan; Kulaksız, Ahmet Afşin

doi:10.1016/j.ijepes.2020.106149

Cited by 43 publications

(22 citation statements)

References 45 publications

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“…The control strategies are highly influenced by the integration of the MPPT algorithm for the WECS. Therefore, these advanced control techniques must produce minimum disturbances when these MPPT algorithms are implemented for WECS [28][29][30][31].…”

Section: P =mentioning

confidence: 99%

A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

Pande

Nasikkar

Kotecha

et al. 2021

JMSE

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Renewable energy resources are gaining a lot of popularity. Several researchers have worked on the tracking and extraction of energy from these sources. In the past few decades, among the available green energy resources, wind energy has been the most attractive option among the resources available. It is imperative to use the maximum power available in the wind to achieve the wind turbine (WT) operation at maximum power. The maximum power point tracking (MPPT) algorithms are a pioneer in this context. Many research papers are contributed in this domain which necessitates a thorough review while choosing an appropriate technique. This paper comprehensively focuses on reviewing different algorithms in the past and present for tracking maximum power point, and capturing maximized output power from the wind energy conversion system (WECS). In this paper, the algorithms are classified based on the direct and indirect power measurement, hybrid and smart algorithms for tracking maximum power point, and they are compared, considering the parameters like complexity, convergence speed, use of sensors, memory requirement, need for knowledge of system parameters, etc. The immense popularity of the different versions of perturb and observe (P&O) based algorithms due to their various features is evident from the literature. The review reveals that the hybrid maximum power point tracking algorithms can use the advantages of the conventional methods and eliminate their drawbacks.

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Section: P =mentioning

confidence: 99%

A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

Pande

Nasikkar

Kotecha

et al. 2021

JMSE

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“…Research in linear controller mainly contains PID controller [17][18][19], robust controller based on the linear matrix inequality approach LMI [20,21], and linear quadratic control LQR [21]. The nonlinear control component mainly contains in many studies predictive control methods PC [22][23][24][25][26][27][28][29] and some intelligent control methods such as neural, fuzzy and sliding mode control [17,[30][31][32][33][34][35]. Because a wind turbine is a multi-input, multi-output system that has strongly nonlinear dynamics, the effect of nonlinear control is better than linear control [36].…”

Section: Literature Reviewmentioning

confidence: 99%

“…References [30-35, 43, 44] present an efficient MPPT methods which does not require any knowledge of the turbine characteristics (methods without wind speed measurement models). These type of control methods are mainly on the Optimal Torque Control (OTC) [14,15], Perturb and Observe (P&O) [43][44][45], Hill-Climbing Search (HCS) [46], Backstepping Control (BSC) [47], Sliding Mode control (SM) [33,34] and various recent artificial intelligence techniques like Fuzzy Logic (FLC) [20,21], Artificial Neural Network method (ANN) [30], Particle Swarm Optimization (PSO) [48], it manages to reach the maximum energy extraction except that its rapidity is reduced especially in the presence of variation in wind speed.…”

Section: Literature Reviewmentioning

confidence: 99%

Nonlinear Predictive Control Method for Maximizing Wind Energy Extraction of Variable Speed Wind Turbines under Turbulence

Aissaoui¹,

Khouidmi²,

Benzouaoui³

et al. 2021

JESA

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Generally, wind turbines are controlled by Maximum Power Point Tracking (MPPT) strategies in order to achieve maximum power extraction below its rated value. But it is very difficult to adjust the rotor speed according to the highly fluctuating wind speed accurately and quickly, due to the large inertia of wind turbines, and therefore, the efficiency of wind energy extraction will never reach its theoretical maximum value. To address this problem, a new method has been developed in this paper which is totally different from the known classical methods. In this paper a wind speeds prediction for maximum wind energy extraction (MWEE) of variable-speed wind turbines (VSWTs) is presented. A nonlinear predictive control is developed by solving a nonlinear optimization problem to generate the optimal generator torque sequence and consequently the previewed rotor speeds with maximum wind energy extraction. A detailed explanation has been provided of how this new method works through a detailed block diagram; accurate algorithm and flowchart. The proposed nonlinear predictive method takes full advantage and the MWEE objective is confirmed by the simulation results compared to the classical TSR methods.

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“…Thus, in [9] using nonlinear perturbation observers for WECS based on doubly fed induction generator (DFIG), a robust SMC is suggested to improve fault ride-through (FRT), while a high-order SMC, which comprises second-order (SO-SMC), is developed to mitigate chattering, hence reducing mechanical stresses and ensured better performances [10]- [14]. Indeed, a maximum power point tracking (MPPT) control based on voltage-mode second-order fast terminal SMC (SO-FTSMC) is proposed to optimize the performance in the power extraction from PMSG based on WECS [12]. Whereas the regulation of the power produced by the generator for a DFIG based wind turbine (WT) is studied using a SO-SMC [13].…”

Section: Introductionmentioning

confidence: 99%

Super-twisting SMC for MPPT and grid-connected WECS based on SCIG

Amina

Mohammed

Houari³

2021

IJPEDS

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This paper proposes a high-order sliding mode control (HO-SMC) with the super-twisting (ST) algorithm for maximum power point tracking (MPPT) and grid-connected wind energy conversion system (WECS), based on squirrel-cage induction generator (SCIG). The main features of this control strategy are attenuation of the chattering phenomenon inherent in first-order sliding mode control and its robustness against external and internal disturbances encountered by the wind power system. The simulation is carried out under SimPowerSystems of MATLAB/Simulink to evaluate the performance and effectiveness of the proposed control compared with conventional and fuzzy logic proportional-integral (PI) controllers for three different scenarios of disturbances, a fluctuating wind speed, a grid voltage drop, and parametric variations.

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Second-order sliding mode voltage-regulator for improving MPPT efficiency of PMSG-based WECS

Cited by 43 publications

References 45 publications

A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

Nonlinear Predictive Control Method for Maximizing Wind Energy Extraction of Variable Speed Wind Turbines under Turbulence

Super-twisting SMC for MPPT and grid-connected WECS based on SCIG

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