Evaluation of ANN estimation-based MPPT control for a DFIG wind turbine

Wei, Chun; Qu, Liyan; Wang, Qiao

doi:10.1109/pemwa.2014.6912224

Cited by 14 publications

(11 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The DFIG in a WECS is usually controlled by a stator flux/voltage oriented vector control method, which, however, requires coordinate transformations and is subject to the problems of slow dynamic response, high sensitivity to system parameter variations and tedious parameter tuning for the proportionalintegral (PI) controllers [1]- [2].…”

Section: Introductionmentioning

confidence: 99%

Sliding-mode observer-based sensorless direct power control of DFIGs for wind power applications

Wei

Wang

Zhao

2015

2015 IEEE Power &Amp; Energy Society General Meeting

Self Cite

View full text Add to dashboard Cite

This paper proposes a novel rotor position estimation algorithm used for reference frame transformation in the direct power control (DPC) of a doubly-fed induction generator (DFIG) in wind power applications. The proposed algorithm can be used as a primary rotor position information provider to replace the rotor position sensor or a backup rotor position information provider during the malfunction of the rotor position sensor to achieve secure and stable operations of the wind power generation system. The proposed rotor position estimation algorithm is based on a nonlinear sliding-mode observer (SMO), which has the advantages such as parameter insensitivity and high robustness to system structure uncertainty. The proposed SMO only requires the information of the stator resistance and inductance while the proportional-integral (PI) controller is not required, thus simplifying the system design by removing the need of tuning PI parameters. The effectiveness of the proposed sensorless DPC scheme is confirmed by the simulation results for a 2-MW-DFIG system in MATLAB/Simulink. Index Terms-Direct power control (DPC), doubly-fed induction generator (DFIG), sensorless control, sliding-mode observer (SMO).I.

show abstract

Section: Introductionmentioning

confidence: 99%

Sliding-mode observer-based sensorless direct power control of DFIGs for wind power applications

Wei

Wang

Zhao

2015

2015 IEEE Power &Amp; Energy Society General Meeting

Self Cite

View full text Add to dashboard Cite

show abstract

“…e energy crisis caused by the longterm consumption of fossil energy and the global demand for clean energy promotes the development of renewable energy. Wind power, solar power, and plug-in electric vehicles have been widely developed in the last decade and might become the main alternatives in the power system in the near future [3,4]. But at the same time, the introduction of these renewable energy sources will bring more complex planning and uncertainty to the power grid production [5].…”

Section: Introductionmentioning

confidence: 99%

A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch

Yang

2020

Complexity

View full text Add to dashboard Cite

Dynamic economic and environmental load dispatch (DEED) aims to determine the amount of electricity generated from power plants during the planning period to meet load demand while minimizing energy consumption costs and environmental pollution emission indicators subject to the operation requirements. This planning problem is usually expressed using a nonsmooth cost function, taking into account various equality and inequality constraints such as valve-point effects, operational limits, power balance, and ramp rate limits. This paper presents DEED models developed for a system consisting of thermal units, wind power generators, photovoltaic (PV) generators, and energy storage (ES). A selection hyper-heuristic algorithm is proposed to solve the problems. Three heuristic mutation operators formed a low-level operator pool to direct search the solution space of DEED. The high level of SHHA evaluates the performances of the low-level operators and dynamically adjusts the chosen probability of each operator. Simulation experiments were carried out on four systems of different types or sizes. The results verified the effectiveness of the proposed method.

show abstract

“…At the highly variable operating points due to uncertain wind speed, conventional controllers like PID refuses to reduce the large fluctuations in electromagnetic torque and also to fulfill the demands of robust MPPT. Therefore, the application of artificial intelligence (AI) based controllers like fuzzy logic, 13,14 artificial neural network (ANN), 15,16 and optimization algorithms 17,18 have been implemented in the MPPT control loop to avail the better efficiency of the wind turbine effectively. However, these MPPT methods have the problem of computational complications that bound their effective utilization in the industry over the classical MPPT methods.…”

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

View full text Add to dashboard Cite

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.

show abstract

Evaluation of ANN estimation-based MPPT control for a DFIG wind turbine

Cited by 14 publications

References 13 publications

Sliding-mode observer-based sensorless direct power control of DFIGs for wind power applications

Sliding-mode observer-based sensorless direct power control of DFIGs for wind power applications

A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch

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

Contact Info

Product

Resources

About