A Robust Online Adaptive B-Spline MPPT Control of Three-Phase Grid-Coupled Photovoltaic Systems Under Real Partial Shading Condition

Kamal, Tariq; Karabacak, Murat; Hassan, Syed Zulqadar; Li, Hui; Fernández‐Ramírez, Luis M.

doi:10.1109/tec.2018.2878358

Cited by 15 publications

(11 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to solve these issues, the modified intelligent algorithms are put forward. Kamal et al [17] have proposed a online adaptive neuro-fuzzy algorithm that incorporates B-spline function from the conventional neurofuzzy. A novel overall distribution (OD) method based on particle swarm optimization has been proposed by Li et al [18].…”

Section: Introductionmentioning

confidence: 99%

A Modified Hybrid Maximum Power Point Tracking Method for Photovoltaic Arrays Under Partially Shading Condition

Zhang

Zhou

et al. 2019

IEEE Access

View full text Add to dashboard Cite

To ensure the photovoltaic (PV) arrays under partial shading condition(PSC) could still output maximum power quickly and efficiently, this work presents a modified hybrid maximum power point tracking (MPPT) method, which applies artificial neural network (ANN) to the modified perturb and observe (MP&O). Instead of using expensive illumination intensity sensors directly, the illumination intensity on each module in the PV array can be obtained indirectly by sampling the specific points of their own cheaper voltage-current sensors. ANN uses indirect illumination intensity to predict the optimal voltage areas of the global maximum power point (GMPP). Based on the areas, MP&O adopts a adaptive step size strategy to obtain GMPP. By modeling and simulation in Matlab/Simulink, it is shown that the tracking time and efficiency of the proposed method in this work can reach 0.026s and 99.87% respectively. Compared with other methods, the method has faster speed, higher efficiency, smaller fluctuation and lower complexity.

show abstract

Section: Introductionmentioning

confidence: 99%

A Modified Hybrid Maximum Power Point Tracking Method for Photovoltaic Arrays Under Partially Shading Condition

Zhang

Zhou

et al. 2019

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In [24] the tracking time error estimated was 1.58s. For further evaluation, Table 3 illustrates the results presented in [45]- [46] such as Third Order B-spline Adaptive Neuro-fuzzy Controller (TOANC), fuzzy logic controller, PID-incremental conductance (PID-InCon) and PID-Hill climbing (PID-HC). As can be observed, TOANC achieved the highest efficiency and the lowest error as it employed the MPPT error and its derivative.…”

Section: Resultsmentioning

confidence: 99%

“…The maximum power is transferred to the load when R eq is equal to the output resistance (R o ) of the PV system [45]- [46]. Hence, according to the maximum power transfer theorem the duty cycle can be obtained as follows:…”

Section: Design the Dc-dc Convertermentioning

confidence: 99%

A Highly-Efficient Fuzzy-Based Controller With High Reduction Inputs and Membership Functions for a Grid-Connected Photovoltaic System

et al. 2020

View full text Add to dashboard Cite

Most conventional Fuzzy Logic Controller (FLC) rules are based on the knowledge and experience of expert operators: given a specific input, FLCs produce the same output. However, FLCs do not perform very well when dealing with complex problems that comprise several input variables. Hence, an optimization tool is highly desirable to reduce the number of inputs and consequently maximize the controller performance, leading to easier maintenance and implementation. This paper, presents an enhanced fuzzy logic controller applied to a photovoltaic system. Specifically, both inputs and membership functions are reduced, resulting in a Highly Reduced Fuzzy Logic Controller (HRFLC), to model a 100kW gridconnected Photovoltaic Panel (PV) as part of a Maximum Power Point Tracking (MPPT) scheme. A DC to DC boost converter is included to transfer the total energy to the grid over a three-level Voltage Source Converter (VSC), which is controlled by varying its duty cycle. FLC generates control parameters to simulate different weather conditions. In this study, only one input representing the current variation (I) of the FLC is used to provide an effective and accurate solution. This reduction in simulation inputs results in a novel HRFLC which simplifies the solar electric system design with output Membership Functions (MFs). Both are achieved by grouping two rules instead of using an existing state-of-the-art method with twenty-five MFs. To the best of our knowledge, this is the first FLC able to provide such rules compression. Finally, a comparison with different techniques such as Perturb and Observe (P&O) shows that HRFLC can improve the dynamic and the steady state performance of the PV system. Notably, experimental results report a steady state error of 0.119%, a transient time of 0.28s and an MPPT tracking accuracy of 0.009s.

show abstract

“…Researchers developed various techniques to extract maximum power from the PV sources. Some of the MPPT techniques are perturb and observe (P&O) [5][6][7], hill climbing (HC) [8], incremental conductance (IncCond) [9,10], fractional voltage/current MPPT control [11], fuzzy-logic (FL) [12,13], neural network (NN) [14,15], optimization techniques [16], and sliding mode (SM) control [17][18][19]. Among the conventional MPPT techniques, P&O and the IncCond techniques are widely used due to their simplicity yet being efficient [20].…”

Section: Introductionmentioning

confidence: 99%

“…Other machine learning MPPT techniques, e.g. NN [14], FL [12], SM [17], and optimization techniques, show improved performance. But these are not commonly used due to need of expensive controllers and complexity for implementation and big data processing for the training of the system to enhance the tracking accuracy [22].…”

Section: Introductionmentioning

confidence: 99%

A current sensor based adaptive step‐size MPPT with SEPIC converter for photovoltaic systems

Kumar

Ghosh

Naidu

et al. 2021

IET Renewable Power Gen

View full text Add to dashboard Cite

Efficient maximum power point tracking (MPPT) is an important problem for renewable power generation from photovoltaic systems. In this work, a current sensor based MPPT algorithm using an adaptive step-size for a single ended primary inductance converter (SEPIC) based solar photovoltaic system is proposed. Due to lower sensitivity of power to current perturbation as compared to the voltage one, such a scheme is shown to yield better efficiency at steady-state. A new adaptation scheme is also proposed for faster convergence of the MPPT technique. Hence, the proposed scheme yields better transient as well as steady-state performance. A prototype converter is used along with digital implementation of the proposed MPPT technique to demonstrate the superiority of the proposed algorithm over the fixed step-size and voltage based ones. Simulation and experimental results corroborates the same. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

A Robust Online Adaptive B-Spline MPPT Control of Three-Phase Grid-Coupled Photovoltaic Systems Under Real Partial Shading Condition

Cited by 15 publications

References 37 publications

A Modified Hybrid Maximum Power Point Tracking Method for Photovoltaic Arrays Under Partially Shading Condition

A Modified Hybrid Maximum Power Point Tracking Method for Photovoltaic Arrays Under Partially Shading Condition

A Highly-Efficient Fuzzy-Based Controller With High Reduction Inputs and Membership Functions for a Grid-Connected Photovoltaic System

A current sensor based adaptive step‐size MPPT with SEPIC converter for photovoltaic systems

Contact Info

Product

Resources

About