Ripple Correlation Control Maximum Power Point Tracking for Battery Operated PV Systems: A Comparative analysis

Sahu, Pankaj; Sharma, Ashish Kumar; Dey, Rajiv

doi:10.1109/iemtronics51293.2020.9216414

Cited by 10 publications

(3 citation statements)

References 22 publications

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“…In [14] study provides an analytical comparison for RCC, P&O and IC at different irradiations. The simulation results show that P&O is greatly affected by slow tracking and fluctuations, and IC achieves better than P&O in terms of tracking, but not for ripples.…”

Section: Mppt Controller Methodsmentioning

confidence: 99%

Maximum Power Point Tracker Controller Using Fuzzy Logic Control with Battery Load for Photovoltaics Systems

Baramadeh¹,

Abou-Elela²,

Alghuwainem³

2021

SGRE

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Section: Mppt Controller Methodsmentioning

confidence: 99%

Maximum Power Point Tracker Controller Using Fuzzy Logic Control with Battery Load for Photovoltaics Systems

Baramadeh¹,

Abou-Elela²,

Alghuwainem³

2021

SGRE

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“…To overcome this disadvantage, more advanced and durable techniques have been developed. Perturb & Observe-PO [18,19], Incremental Conductance-IC [20,21], Constant Voltage-CV [22,23], Adaptive Reference Voltage-ARV [24], Constant Current-CC [25,26], Hill Climbing-HC [27,28], Parasitic Capacitance-PC [7.29], Fractional Open Circuit Voltage-FOCV [30], Fractional Short Circuit Current-FSCC [31], Ripple Correlation Control-RCC [32], DC-Link Capacitor Drop [33,34], On-Line MPP [35], Lookup Table [36], Linearization-based MPPT [37,38] are the conventional MPPT methods [39,17]. Among them, PO, IC, CV, and ARV methods are widely used.…”

Section: Introductionmentioning

confidence: 99%

System Identification Based ARV-MPPT Technique for PV Systems Under Variable Atmospheric Conditions

Gündoğdu

2022

IEEE Access

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Different tracking algorithms have been developed to obtain maximum efficiency from the PV power systems under changing atmospheric conditions. Some of these algorithms are effective under uniform irradiance, while the others are effective under partial shading conditions. In this study, a new MPPT method designed with System Identification-SI and named SI-based polynomial ARV is proposed for a PV system under uniform irradiance. The recommended method is also an adaptive reference voltage-ARV-based method. In this method, the model in which the reference voltage is obtained has a simple polynomial structure. This polynomial model has been obtained by assuming that the PV system is a nonlinear black-box type system. The input-output data, which are required for modeling, were created in MATLAB/Simulink environment. Then, by using these data with SI-Toolbox, the mathematical model of the PV system in polynomial structure giving the input-output relationship was obtained. T temperature information was used as model input, which was the generated reference voltage. Simulation studies were carried out under two different changing atmospheric scenarios; and the performance of the proposed method was analyzed. The obtained results were compared with perturb & observe-PO, incremental conductance-IC, constant voltage reference-CVR, artificial neural network-ANN-based ARV, and SI-based nonlinear ARV methods. All simulation results showed that the recommended method is simple structured, applicable, and has high performance.

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“…This method of design is very easy because it doesn't require many more components for the development of a ripple correlation-based sunlight system. Here, by using the ripple correlation block, the proposed system implementation price is improved which is not acceptable for domestic consumers 15 .…”

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confidence: 99%

A new wide input voltage DC-DC converter for solar PV systems with hybrid MPPT controller

Kumar,

Balakrishna

2024

Sci Rep

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The present working conventional power generation systems utilization is reducing day by day because of their demerits are more functioning cost, high carbon dioxide emission, more complexity in handling, and required high installation area. So, the current power generation company focuses on Renewable Energy Sources (RES) which are wind, tidal, and solar. Here, the solar power network is utilized for supplying electricity to the electrical vehicle battery charging system. The Solar photovoltaic (PV) modules supply nonlinear power which is not useful for automotive systems. To maximize the supply power of the solar PV system, an Adaptive Step Genetic Algorithm Optimized (ASGAO) Radial Basis Functional Network (RBFN) is utilized for tracking the working point of the solar PV module thereby enhancing the operating efficiency of the overall system. The features of this proposed hybrid Maximum Power Point Tracking (MPPT) controller are quick system dynamic response, easy operation, quick convergence speed, more robustness, and high operating efficiency when equalized with the basic MPPT controllers. The major issue of solar PV modules is low supply voltage which is increased by introducing the wide input voltage DC-DC converter. The merits of this introduced converter are low-level voltage stress on diodes, good quality supply power, high voltage gain, plus low implementation cost. Here, the introduced converter along with the AGAO-RBFN controller is analyzed by selecting the MATLAB/Simulink environment. Also, the proposed converter is tested with the help of a programable DC source.

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Ripple Correlation Control Maximum Power Point Tracking for Battery Operated PV Systems: A Comparative analysis

Cited by 10 publications

References 22 publications

Maximum Power Point Tracker Controller Using Fuzzy Logic Control with Battery Load for Photovoltaics Systems

Maximum Power Point Tracker Controller Using Fuzzy Logic Control with Battery Load for Photovoltaics Systems

System Identification Based ARV-MPPT Technique for PV Systems Under Variable Atmospheric Conditions

A new wide input voltage DC-DC converter for solar PV systems with hybrid MPPT controller

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