A novel MPPT method for enhancing energy conversion efficiency taking power smoothing into account

Liu, Jizhen; Meng, Hongmin; Hu, Yang; Lin, Zongli; Wang, Wei

doi:10.1016/j.enconman.2015.06.005

Cited by 75 publications

(42 citation statements)

References 29 publications

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“…The active power is determined by i qs control and the reactive power is determined by i ds control. Details of decoupling control can be found in [3]. It is noted that the generator power discussed in this paper is active power, and the reactive power is set to zero.…”

Section: Description Of the Proposed Frameworkmentioning

confidence: 99%

“…Part 1 is a classical OTC MPPT calculator. OTC is one of the most widely employed MPPT strategies for its good stability, control performance [3,28] and simple implementation. The output of the OTC calculator is expressed as:…”

Section: Description Of the Proposed Frameworkmentioning

confidence: 99%

“…In full-load regime, power smoothing is the main control objective, and it is unnecessary to consider energy conversion efficiency. In partial-load regime, maximum power point tracking (MPPT) is the main operation mode [3,4]. The control objectives in partial-load regime consist of achieving high wind energy conversion efficiency, smoothing output power, diminishing mechanical loads, riding through fault conditions, etc.…”

Section: Introductionmentioning

confidence: 99%

“…A novel MPPT framework employing fuzzy inference system (FIS) was proposed in [3] to consider these multiple objectives. The captured energy efficiency is enhanced, and power fluctuation is suppressed as much as possible, but FIS requires a priori artificial experience, and it is complex to establish fuzzy memberships.…”

Section: Introductionmentioning

confidence: 99%

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A Flexible Maximum Power Point Tracking Control Strategy Considering Both Conversion Efficiency and Power Fluctuation for Large-inertia Wind Turbines

et al. 2017

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Abstract:In wind turbine control, maximum power point tracking (MPPT) control is the main control mode for partial-load regimes. Efficiency potentiation of energy conversion and power smoothing are both two important control objectives in partial-load regime. However, on the one hand, low power fluctuation signifies inefficiency of energy conversion. On the other hand, enhancing efficiency may increase output power fluctuation as well. Thus the two objectives are contradictory and difficult to balance. This paper proposes a flexible MPPT control framework to improve the performance of both conversion efficiency and power smoothing, by adaptively compensating the torque reference value. The compensation was determined by a proposed model predictive control (MPC) method with dynamic weights in the cost function, which improved control performance. The computational burden of the MPC solver was reduced by transforming the cost function representation. Theoretical analysis proved the good stability and robustness. Simulation results showed that the proposed method not only kept efficiency at a high level, but also reduced power fluctuations as much as possible. Therefore, the proposed method could improve wind farm profits and power grid reliability.

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Section: Description Of the Proposed Frameworkmentioning

confidence: 99%

Section: Description Of the Proposed Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Flexible Maximum Power Point Tracking Control Strategy Considering Both Conversion Efficiency and Power Fluctuation for Large-inertia Wind Turbines

et al. 2017

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“…Compared with our country, many foreign countries carried out the research of wind power prediction error distribution earlier, the normal distribution, beta distribution, Cauchy distribution and Laplace distribution and several traditional empirical distribution models were proposed [3][4][5][6] . At the same time, different error distribution models have their own characteristics and the best applicable scope, the normal distribution assumption is the most widely used at present and it was put forward earliest.…”

Section: Introductionmentioning

confidence: 99%

Error Analysis of Ultra Short Term Wind Power Prediction Model

Zhu¹,

Zha²,

Qin³

2017

Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

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Abstract. In this paper, we use a piecewise exponential distribution model to predict the ultra short term wind power error and then estimate the parameters. The case we used is from Northern Ireland, we forecast the probability and precision of wind power on the basis of Normal distribution model, Laplace distribution model, Cauchy distribution model, Beta distribution model and the proposed piecewise exponential distribution model. The prediction error distribution model of the sub index wind power forecasting error can be used to mine the relative information of the actual error distribution, in addition, it's convenient to implement and easy to be used in calculus, it can be applied to describe the error distribution of the multiple time scale prediction, so it has more advantages in the error analysis.

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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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A novel MPPT method for enhancing energy conversion efficiency taking power smoothing into account

Cited by 75 publications

References 29 publications

A Flexible Maximum Power Point Tracking Control Strategy Considering Both Conversion Efficiency and Power Fluctuation for Large-inertia Wind Turbines

A Flexible Maximum Power Point Tracking Control Strategy Considering Both Conversion Efficiency and Power Fluctuation for Large-inertia Wind Turbines

Error Analysis of Ultra Short Term Wind Power Prediction Model

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

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