An Application of Intelligent Non-linear Discrete-PID Controller for MPPT of PV System

Pathak, Diwaker; Sagar, Gautam; Gaur, Prerna

doi:10.1016/j.procs.2020.03.368

Cited by 28 publications

(9 citation statements)

References 9 publications

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“…The proportional-integral-derivative (PID) controller is simple to use and set up, and it is widely used in industrial applications for speed control of dc motors due to its proper control performance and lack of complexity in design [8], [13], [14]. The PID controller form is shown in (8).…”

Section: Pid Controllermentioning

confidence: 99%

Implementing optimization of PID controller for DC motor speed control

Rashid

Hussain

2021

IJEECS

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The point of this paper presents an optimization technique which is flexible and quick tuning by using a genetic algorithm (GA) to obtain the optimum proportional-integral-derivative (PID) parameters for speed control of aseparately excited DC motor as a benchmark for performance analysis. The optimization method is used for searching for the proper value of PID parameters. The speed controller of DC motor using PID tuning method sincludes three types: MATALB PID tunner app., modified Ziegler-Nicholsmethod and genetic algorithm (GA). PID controller parameters (Kp, Ki and Kd) will be obtained by GA to produce optimal performance for the DC motor control system. Simulation results indicate that the tuning method of PID by using a genetic algorithm is shown to create the finest result in system performance such as settling time, rise time, percentage of overshoot and steady state error. The MATLAB/Simulink software is used to model and simulate the proposed DC motor controller system.

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Section: Pid Controllermentioning

confidence: 99%

Implementing optimization of PID controller for DC motor speed control

Rashid

Hussain

2021

IJEECS

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“…where k p , k i , k d , and e are proportional, integral, and derivative gains and error, respectively. T s is the sampling time of the model, which can be determined using the expression (20).…”

Section: Maximum Power Point Trackingmentioning

confidence: 99%

“…Nevertheless, the use of the fuzzy logic based MPPT method needs the complete information of the WECS operation and also, the fuzzy logic rule-base may lead to comprehensive calculations, if not well-designed. 14 Various applications of AI controllers in MPPT methods have been extensively implemented in the renewable energy field that is, in solar energy, [20][21][22][23] and wind energy due to their capability of elimination of large oscillations in electromagnetic torque. Nevertheless, they have shortcomings such as algorithmic complications, the requirement of additional hardware set-up, extra tuning factors, needs a huge memory, higher simulation time, and therefore, hard to implement.…”

Section: Introductionmentioning

confidence: 99%

“…Various applications of AI controllers in MPPT methods have been extensively implemented in the renewable energy field that is, in solar energy, 20‐23 and wind energy due to their capability of elimination of large oscillations in electromagnetic torque. Nevertheless, they have shortcomings such as algorithmic complications, the requirement of additional hardware set‐up, extra tuning factors, needs a huge memory, higher simulation time, and therefore, hard to implement 24 .…”

Section: Introductionmentioning

confidence: 99%

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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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“…With the variation in wind speed, the MPP power reference for the WECS varies as well. A discrete-time PID controller with fixed gains regulates the instantaneous value of rotor mechanical speed to its reference value by processing the error between two, following the control output transfer function stated as [23]:…”

Section: A Pid Controllermentioning

confidence: 99%

Hybrid Fuzzy-PID based MPPT Enhancement of Grid-Connected DFIG Wind Energy Eystem with TLBO Optimization

Bhati¹,

Gaur²

2020

IJERT

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This research article emphasizes the enhancement of Maximum Power Point Tracking (MPPT) action using a Fuzzy supervised PID (f-PID) controller for a grid-connected 2MW Doubly fed Induction Generator (DFIG) connected to a passive filter and grid via Back-to-Back PWM Converter topology. This article also proposes the implementation of Teaching Learningbased optimization (TLBO) technique for tuning gain parameters of the proposed as well as extant controllers used in the MPPT algorithm. The primary objective is to improvise the conventional Rotor side current-based field-oriented control (MSC) of the understudy system, by employing a modified Tip-Speed Ratio (TSR) based MPPT algorithm with wind speed estimator. This algorithm ensures extraction and regulation of maximum active power while minimizing stator reactive power drawn under a step-wise variable wind speed profile. It is realized by employing a PID controller to restrict rotor angular speed variation around its optimal value, estimated by a fuzzy logic system. After the completion of a comprehensive simulation analysis using MATLAB/Simulink R2017a, the performance of the proposed controller in steady as well as transient states is being fairly found to be superior as compared to that of PID and Non-linear PID (NPID) based controllers in terms of settling time, MPP steady-state error and tracking efficiency.

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An Application of Intelligent Non-linear Discrete-PID Controller for MPPT of PV System

Cited by 28 publications

References 9 publications

Implementing optimization of PID controller for DC motor speed control

Implementing optimization of PID controller for DC motor speed control

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

Hybrid Fuzzy-PID based MPPT Enhancement of Grid-Connected DFIG Wind Energy Eystem with TLBO Optimization

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