A fuzzy-logic based auto-scaling variable step-size MPPT method for PV systems

Chen, Yie‐Tone; Jhang, Yi-Cheng; Liang, Rung-Huei

doi:10.1016/j.solener.2016.01.007

Cited by 116 publications

(40 citation statements)

References 26 publications

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“…The current step size is adjusted and confirmed based on the variation in the power value and the duty ratio at the last moment. The input of the fuzzy controller at moment is the variation in the power value in the photovoltaic system at moment and the step size of the duty ratio [9,10] at moment −1, while the output at moment is the step size of the duty ratio at moment . Thus, the fuzzy controller designing this study is as shown in Figure 4, where and are the quantization factors.…”

Section: Design Of Mppt Fuzzy Control Based On Pando Methodmentioning

confidence: 99%

Application of Fuzzy Control in a Photovoltaic Grid-Connected Inverter

Zheng

Zhang

Xue

2018

Journal of Electrical and Computer Engineering

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To realize the maximum power output of a grid-connected inverter, the MPPT (maximum power point tracking) control method is needed. The perturbation and observation (P&O) method can cause the inverter operating point to oscillate near the maximum power. In this paper, the fuzzy control P&O method is proposed, and the fuzzy control algorithm is applied to the disturbance observation method. The simulation results of the P&O method with fuzzy control and the traditional P&O method prove that not only can the new method reduce the power loss caused by inverter oscillation during maximum power point tracking, but also it has the advantage of speed. Inductive loads in the post-grid-connected stage cause grid-connected current distortion. A fuzzy control algorithm is added to the traditional deadbeat grid-connected control method to improve the quality of the system's grid-connected operation. The fuzzy deadbeat control method is verified by experiments, and the harmonic current of the grid-connected current is less than 3%.

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Section: Design Of Mppt Fuzzy Control Based On Pando Methodmentioning

confidence: 99%

Application of Fuzzy Control in a Photovoltaic Grid-Connected Inverter

Zheng

Zhang

Xue

2018

Journal of Electrical and Computer Engineering

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“…Recently, FLC was used for MPPT, including fuzzification, inference rule, and defuzzification. In FLC, the errors are used as inputs and the output can be the change in the generated voltage or duty cycle . Similar to ANN, this technique may be incorporated with classic MPPT techniques to achieve better performance.…”

Section: Different Designs and Algorithms In Reducing Thd In Pv Systemsmentioning

confidence: 99%

Advances in reduction of total harmonic distortion in solar photovoltaic systems: A literature review

Alhafadhi

Teh

2019

Int J Energy Res

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Summary The use of photovoltaic (PV) systems has increased in recent years due to the high demand for clean energy sources. PV systems can utilize abundant and free energy from the sun, which is a substantial advantage. However, compared with other renewable technologies, the PV system still faces major obstacles such as high cost and low efficiency. In addition, fluctuating incident energy from the sun creates harmonics in the generated power that might lead to undesirable system performance. Total harmonic distortion (THD) is the ratio of distorted power to the main power of the signal, and is most commonly used to indicate the amount of signal distortion. THD has become a serious concern as more PV systems are integrated into grid systems. Previous research and reviews have attempted to reduce THD and its effect, but unfortunately focused on reducing THD at individual parts of the PV system. For the first time, this study holistically and systematically reviews the advances in THD reduction techniques for the entire PV system. The causes of harmonics, current solutions, and research gaps for further investigation are described in detail. Moreover, the current THD reduction techniques used in each stage of the PV system are compared, including their main benefits and drawbacks. Finally, this study recommends the use of adaptive filters as a possible solution for THD reduction because these filters have effectively reduced noise and disturbance in other systems.

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“…This configuration allowed the use of static backpropagation [25], with Levenberg-Marquardt optimization [33] for the network training. Where the new input P and the network target T are shown in Equation (14).…”

Section: Neural Network Inverse Model Controllermentioning

confidence: 99%

“…The NARX was configured with an input (power) and an output (duty cycle). The network is made of a hidden layer of 10 neurons with a Tansig (Tangent sigmoid) Where the new input P and the network target T are shown in Equation (14).…”

Section: Neural Network Inverse Model Controllermentioning

confidence: 99%

A Low-Cost Maximum Power Point Tracking System Based on Neural Network Inverse Model Controller

Robles-Algarín¹,

Hernández²,

Leal³

2018

Electronics

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This work presents the design, modeling, and implementation of a neural network inverse model controller for tracking the maximum power point of a photovoltaic (PV) module. A nonlinear autoregressive network with exogenous inputs (NARX) was implemented in a serial-parallel architecture. The PV module mathematical modeling was developed, a buck converter was designed to operate in the continuous conduction mode with a switching frequency of 20 KHz, and the dynamic neural controller was designed using the Neural Network Toolbox from Matlab/Simulink (MathWorks, Natick, MA, USA), and it was implemented on an open-hardware Arduino Mega board. To obtain the reference signals for the NARX and determine the 65 W PV module behavior, a system made of a 0.8 W PV cell, a temperature sensor, a voltage sensor and a static neural network, was used. To evaluate performance a comparison with the P&O traditional algorithm was done in terms of response time and oscillations around the operating point. Simulation results demonstrated the superiority of neural controller over the P&O. Implementation results showed that approximately the same power is obtained with both controllers, but the P&O controller presents oscillations between 7 W and 10 W, in contrast to the inverse controller, which had oscillations between 1 W and 2 W.

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A fuzzy-logic based auto-scaling variable step-size MPPT method for PV systems

Cited by 116 publications

References 26 publications

Application of Fuzzy Control in a Photovoltaic Grid-Connected Inverter

Application of Fuzzy Control in a Photovoltaic Grid-Connected Inverter

Advances in reduction of total harmonic distortion in solar photovoltaic systems: A literature review

A Low-Cost Maximum Power Point Tracking System Based on Neural Network Inverse Model Controller

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