Steady Output and Fast Tracking MPPT (SOFT-MPPT) for P&amp;O and InC Algorithms

Bhattacharyya, Shamik; P, Dattu Sampath Kumar; Samanta, Susovon; Mishra, Sukumar

doi:10.1109/tste.2020.2991768

Cited by 188 publications

(92 citation statements)

References 19 publications

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“…In the developed methods, the main goal is to achieve speed, high efficiency, and high adaptability to environmental conditions [17][18][19][20]. In another study, a new soft-MPPT algorithm that could be realized with low-level microprocessors and also used in conjunction with both PO and INC algorithms was proposed [21]. Both simulation and experimental study of the INC method used in conjunction with the CUK converter were carried out and compared [22].…”

Section: Introductionmentioning

confidence: 99%

Comparison of PO and INC MPPT Methods Using FPGA In-The-Loop Under Different Radiation Conditions

Çelikel

Gündoğdu

2021

Balkan Journal of Electrical and Computer Engineering

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In photovoltaic (PV) systems, the Maximum Power Point Tracking (MPPT) algorithms are applied to obtain maximum efficiency under different atmospheric conditions. Among the MPPT methods, Perturb & Observe (PO) and Incremental Conductance (INC) methods are the oldest algorithms that have been used. Field Programmable Gate Arrays (FPGA) are used especially in applications requiring high speed. FPGA in-the-loop feature is used to test algorithms designed in MATLAB/Simulink environment. In this study, PO and INC methods were designed to work in FPGA environment. Both algorithms were tested under different radiation conditions by using FPGA-in-the-loop feature. The FPGA in-the-loop simulation result of PO and INC methods was shown graphically. Altera DE2-115 development board was used to test PO and INC MPPT algorithms. In addition, PO and INC methods were synthesized using the Quartus-II program. Comparisons of the simplicity of the algorithms were made based on the synthesis results. Thus, by using the FGPA in-the-loop feature and performing the synthesis process, both of the algorithms were tested and the areas covered by the algorithms in the FPGA were compared.

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Section: Introductionmentioning

confidence: 99%

Comparison of PO and INC MPPT Methods Using FPGA In-The-Loop Under Different Radiation Conditions

Çelikel

Gündoğdu

2021

Balkan Journal of Electrical and Computer Engineering

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“…The advantage of this method is that the control structure is simple. Following connection to the grid, the inner loop controls the inductor's current and the outer loop controls the DC voltage, and can thus send all of the PV power into the grid [8,9]. However, the disadvantage of this method is that the control strategy needs to change to switch the control mode between off-grid and grid-connected.…”

Section: Introductionmentioning

confidence: 99%

A United Control Strategy of Photovoltaic-Battery Energy Storage System Based on Voltage-Frequency Controlled VSG

Yan

Wang

et al. 2021

Electronics

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At present, the installed capacity of photovoltaic-battery energy storage systems (PV-BESs) is rapidly increasing. In the traditional control method, the PV-BES needs to switch the control mode between off-grid and grid-connected states. Thus, the traditional control mode reduces the reliability of the system. In addition, if the system is accidentally disconnected from the grid or the energy storage battery fails to work normally, the DC voltage of the inverter increases or decreases rapidly. To address these two problems, in this paper, a united control strategy is proposed. In the case of grid connection, based on the voltage-frequency controlled VSG strategy, the strategy adjusts the output power of the VSG by changing the position of the primary frequency modulation curve. This method can ensure that, after the system is connected to the grid, excess PV power can be sent to the grid, or power can be absorbed from the grid to charge energy storage. In the off-grid state, the strategy uses FPPT technology and superimposes a voltage component onto the voltage loop to quickly balance the DC power and AC power of the inverter. This strategy can improve the reliability of the system’s power supply if the energy storage fails to work normally. Finally, a PV-BES model was built using MATLAB-Simulink, and the simulation results proved the effectiveness of the proposed strategy.

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“…It is considered as one of the most promising renewable energy source (RES) because of its cleanliness, abundance and environmental friendliness, compared with conventional energy sources such as oil, natural gas and fossil fuel [2]. Despite its advantages, the output active power P from solar power system varies according to the solar irradiance E E and opera-tion temperature T, especially under rapid changing partial shading condition (PSC) due to the non-linear characteristic of photovoltaic (PV) cell [3]. The complex relationship between power output with PV input parameters results in unsatisfactory power extraction [4].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Based MPPT Techniques for Solar Power System: A review

Yap

Sarimuthu

Lim

2020

Journal of Modern Power Systems and Clean Energy

194

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In the last decade, artificial intelligence (AI) techniques have been extensively used for maximum power point tracking (MPPT) in the solar power system. This is because conventional MPPT techniques are incapable of tracking the global maximum power point (GMPP) under partial shading condition (PSC). The output curve of the power versus voltage for a solar panel has only one GMPP and multiple local maximum power points (MPPs). The integration of AI in MPPT is crucial to guarantee the tracking of GMPP while increasing the overall efficiency and performance of MPPT. The selection of AI-based MPPT techniques is complicated because each technique has its own merits and demerits. In general, all of the AI-based MPPT techniques exhibit fast convergence speed, less steady-state oscillation and high efficiency, compared with the conventional MPPT techniques. However, the AI-based MPPT techniques are computationally intensive and costly to realize. Overall, the hybrid MPPT is favorable in terms of the balance between performance and complexity, and it combines the advantages of conventional and AI-based MPPT techniques. In this paper, a detailed comparison of classification and performance between 6 major AI-based MPPT techniques have been made based on the review and MATLAB/Simulink simulation results. The merits, open issues and technical implementations of AI-based MPPT techniques are evaluated. We intend to provide new insights into the choice of optimal AI-based MPPT techniques. Index Terms-Maximum power point tracking (MPPT), artificial intelligence (AI), fuzzy logic control (FLC), artificial neural network (ANN), genetic algorithm (GA), swarm intelligence (SI), machine learning (ML).

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Steady Output and Fast Tracking MPPT (SOFT-MPPT) for P&O and InC Algorithms

Cited by 188 publications

References 19 publications

Comparison of PO and INC MPPT Methods Using FPGA In-The-Loop Under Different Radiation Conditions

Comparison of PO and INC MPPT Methods Using FPGA In-The-Loop Under Different Radiation Conditions

A United Control Strategy of Photovoltaic-Battery Energy Storage System Based on Voltage-Frequency Controlled VSG

Artificial Intelligence Based MPPT Techniques for Solar Power System: A review

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