Adaptive fractional-order PID control of PMSG-based wind energy conversion system for MPPT using linear observers

Yang, Bo; Yu, Tao; Shu, Hongchun; Han, Yiming; Cao, Ping; Jiang, Lin

doi:10.1002/etep.2697

Cited by 64 publications

(37 citation statements)

References 32 publications

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“…On the other hand, fractional-order control theories and applications of traditional integer-order and fractional-order systems have attracted increasing attention over the past two decades [24]. The fractional-order PI/PID control algorithm has been considered as one of the most widely and successfully used methods in complex systems, such as servo systems [25,26], a nonlinear vertical tank system [27], electric balance vehicle system [28], an induction motor drive system [29], permanent magnetic synchronous generator [30], automatic voltage regulator systems [31], single-area delayed power systems [32], and multi-area interconnected power systems [33]. One particular concern is the fractional-order frequency control of an isolated microgrid.…”

Section: Introductionmentioning

confidence: 99%

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

et al. 2018

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Optimal frequency control of an islanded microgrid has been a challenging issue in the research field of microgrids. Recently, fractional-order calculus theory and some related control methods have attempted to handle this issue. In this paper, a novel fractional-order model predictive control (FOMPC) method is proposed to achieve the optimal frequency control of an islanded microgrid by introducing a fractional-order integral cost function into model predictive control (MPC) algorithm. Firstly, a discrete state-space model is derived for the optimal frequency control problem of an islanded microgrid. Afterward, a fractional-order integral cost function is designed to guide the FOMPC algorithm to obtain optimal control law by borrowing the Grünwald-Letnikov (GL) definition of fractional order calculus. Six simulation studies have been carried out to illustrate the superiority of FOMPC to conventional MPC under dynamical load disturbances, perturbed system parameters and random dynamical power fluctuation of wind turbines.

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Section: Introductionmentioning

confidence: 99%

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

et al. 2018

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“…where k 12 , k 13 , k 22 , and k 23 are positive tuning parameters and sat(·) is the saturation function, which is defined as…”

Section: Fosmc Designmentioning

confidence: 99%

“…Nevertheless, the chattering phenomenon limits the implementation of SMC in practice. To tackle the issue, fractional‐order sliding mode control (FOSMC) is proposed based on the integration of SMC method and fractional‐order calculus theory . Different from integer‐order rational transfer functions, the fractional‐order operator possesses the infinite memory and takes into consideration the whole history of input signals, which effectively reduces the chattering phenomenon of conventional SMC .…”

Section: Introductionmentioning

confidence: 99%

“…To tackle the issue, fractional-order sliding mode control (FOSMC) is proposed based on the integration of SMC method and fractional-order calculus theory. 21,22 Different from integer-order rational transfer functions, the fractional-order operator possesses the infinite memory and takes into consideration the whole history of input signals, which effectively reduces the chattering phenomenon of conventional SMC. 23 Passive FOSMC is designed for photovoltaic systems to achieve maximum power point tracking under various operating conditions, and FOSMC greatly improves the robustness of the closed-loop system against various disturbances.…”

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confidence: 99%

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Fractional‐order sliding mode control for damping of subsynchronous control interaction in DFIG‐based wind farms

Xiong

Wang

et al. 2019

Wind Energy

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This paper proposes a fractional-order sliding mode control (FOSMC) based on feedback linearization (FL) technique to mitigate subsynchronous control interaction (SSCI) in doubly fed induction generator (DFIG)-based wind farms connected to series-compensated transmission lines. A linearized form of the studied system is obtained with the use of FL, which leads to reduced system order and small computational burden. Then the FOSMC is designed for grid-side converter (GSC) to stabilize SSCI and to provide a considerable robustness against external disturbances and parameter uncertainties. For FOSMC parameter tuning, genetic algorithm (GA) is performed through MATLAB/SIMULINK. Time-domain simulation are carried out to evaluate the effectiveness of the FOSMC in mitigating SSCI at varied operating conditions, and the superior performance of the proposed control is demonstrated as compared with conventional vector control (VC), feedback linearization sliding mode control (FLSMC), high-order sliding mode control (HOSMC). KEYWORDS doubly fed induction generator, fractional-order sliding mode control, subsynchronous control interaction 1 | INTRODUCTION Subsynchronous resonance (SSR) of wind farms is a condition where wind turbines exchange energy with the grid at one or more natural frequency below the fundamental frequency. 1 A new type of SSR, known as subsynchronous control interaction (SSCI), has been detected worldwide in recent years. 2 Without the involvement of mechanical components, rapidly developing SSCI can lead to serious equipment damage and loss of power generation if proper countermeasures are not taken instantly. Furthermore, many studies have demonstrated that doubly fed induction generator (DFIG) wind farms are susceptible to SSCI due to the active participation of fast-acting converter control. 3,4 Therefore, it is urgent to develop effective SSCI mitigation techniques to ensure the safe operation of grid-connected DFIG-based wind farms.The design of SSCI damping controls has received much attention from industry and academia. A number of control methods using FACTS devices are proposed to mitigate SSCI, such as gate-controlled series capacitor (GCSC), 5 thyristor-controlled series capacitor (TCSC), 6 and static synchronous compensator (STATCOM). 7 As compared with FACTS-based damping controls, modification of wind turbine converter (WTC) control is an economical and convenient solution to SSCI. Since grid-side converter (GSC) has the damping capability similar to STATCOM with an extra advantage of lower cost, various damping methods are proposed based on the improvement of existing GSC control. A washout block is embedded into GSC stator voltage control for SSCI mitigation. 8 A supplemental damping signal is added to the summing junction of GSC's outer control. 9 GSC's d-axis inner control loop is also utilized to alleviate SSCI with speed deviation as input control signal (ICS). 10 GSC provides the greater flexibility of adding SSCI damping controls, but its damping capability is limited to 30% of...

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“…The authors proposed a particle swarm optimization (PSO) tuned adaptive fractional order PID (AFOPID) controller based MPPT method and concluded that the performance of the proposed MPPT method is better as compared to the PID, FOPID, and fuzzy in terms of convergence time, fitness function value and IAE. 30 The proposed AFOPID MPPT method uses a d component of stator current and rotor speed for the steady-state error compensation. However, the overall MPPT approach can be improved by reducing the complexity and computational sensor requirement.…”

Section: Introductionmentioning

confidence: 99%

Fractional‐order nonlinear PID controller based maximum power extraction method for a direct‐driven wind energy system

Pathak

Bhati

Gaur

2020

Int Trans Electr Energ Syst

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Objective To maintain the operation of a wind turbine at its maximum efficiency and for the extraction of maximum power from the wind. Method In this paper, at first, a novel application of fractional‐order nonlinear proportional‐integral‐derivative (FONPID) controller is proposed in the machine side converter (MSC) control loop of a 2 MW grid‐connected wind energy system. Then, the grid side converter (GSC) is controlled to ensure the unity power factor of the understudy system. To extract the maximum power from the wind, the application of the proposed controller is applied to a well‐established TSR MPPT control method, which compares optimal and actual values of rotor speed, and generated error is given to the proposed controller to vary the rotor speed accordingly. Moreover, improved MPPT performance offered by the proposed FONPID controller has also been compared to well‐established existing controllers based TSR MPPT methods. Furthermore, parameters of the proposed and existing controllers in the TSR MPPT control loop are also tuned using teaching‐learning based optimization (TLBO) and obtained performance is compared with the performance of particle swarm optimization (PSO) to show effectiveness. Results The generator speed offered by the proposed FONPID based TSR MPPT method effectively tracks its reference values far better than the extant controller based TSR MPPT method, whereas extant NPID has less overshoot as compared to the extant PID based TSR MPPT method. Conclusion To perform the effective operation of achieving MPP, q‐axis current of the stator has been controlled by the proposed FONPID based TSR MPPT method in such a style that rotor speed can be operated at its optimal value where the generator has the maximum power for given wind speed. DC‐link voltage is controlled at its rated value to guarantee the unity power factor operation using the GSC controller. FONPID based TSR MPPT method provides a better and robust MPPT operation than the PID, NPID, and FOPID controllers based TSR MPPT method. The performance has been assessed in terms of minimized fitness function value, steady‐state error, settling time, and percentage overshoot.

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Adaptive fractional-order PID control of PMSG-based wind energy conversion system for MPPT using linear observers

Cited by 64 publications

References 32 publications

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

Fractional‐order sliding mode control for damping of subsynchronous control interaction in DFIG‐based wind farms

Fractional‐order nonlinear PID controller based maximum power extraction method for a direct‐driven wind energy system

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