A Comprehensive Survey of Maximum Power Tracker Techniques for Photovoltaic System

Sharma, Bal Mukund; Sahay, Kuldeep

doi:10.26634/jee.8.1.2998

Cited by 2 publications

(3 citation statements)

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“…Then, the best chromosomes are decoded according to the coding rules, which are used to establish the initial weights and thresholds of the BP neural network model. Genetic algorithm is used to solve for optimal values and then BPNN training is conducted with the optimal values …”

Section: Research On the Mppt Methods Based On The Bp Neural Network mentioning

confidence: 99%

“…Genetic algorithm is used to solve for optimal values and then BPNN training is conducted with the optimal values. 41,42 For this paper, the ambient temperature and solar intensity are used as input of the BPNN, and the measured maximum power point voltage is used as output of the BPNN. The typical a design of BPNN is that the hidden layers employ the sigmoid function as the transfer function, and the output layer uses a linear function as the transfer function.…”

Section: Bp Neural Network With Ga Optimizedmentioning

confidence: 99%

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Research on the voltage prediction of unmanned aerial vehicle photovoltaic modules based on new combination optimization algorithm

Wang

Shen

2019

Int Trans Electr Energ Syst

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Summary Solar energy is a new energy source that is not only renewable but also available everywhere in the world. Thus, this new energy source is used on solar unmanned aerial vehicles. The use of solar photovoltaic systems (PVS) involves the conversion of solar energy into electricity. A photovoltaic cell is the core part of solar unmanned aerial vehicle (UAV) for providing energy. The solar panels are laid on the wings of solar unmanned aerial vehicles. This paper proposes a new MPPT controller for predicting the voltage to obtain the maximum power from the solar panel. In this paper, on the basis of studying the characteristics of photovoltaic cells, combined with the advantages of the mind evolutionary algorithm (MEA) and back propagation network, this article proposes a new type of BP network modeling structure based on the MEA, which is used for the modeling of photovoltaic cells. First, the MEA is constructed based on topology of a back propagation network. Then, this algorithm is used to obtain the optimal solutions, which are regarded as the initial weights and threshold values of the BP neural network. Finally, the simulation experiment is performed MATLAB software; comparing the different prediction results of the MEA optimization BP Network and genetic algorithm (GA) optimization BP neural network with the simple use of the BP neural network. The simulation results indicate that the optimization of the BP neural network by the MEA decreased the mean absolute percent error (MAPE) and root mean square error (RMSE) evaluation indicators by approximately 64% and 0.0524, respectively, compared with the back propagation neural network (BPNN). Overall, the MEA optimization BP neural network has high precision, small error, and a short training time.

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Section: Research On the Mppt Methods Based On The Bp Neural Network mentioning

confidence: 99%

Section: Bp Neural Network With Ga Optimizedmentioning

confidence: 99%

Research on the voltage prediction of unmanned aerial vehicle photovoltaic modules based on new combination optimization algorithm

Wang

Shen

2019

Int Trans Electr Energ Syst

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“…Paper [36] referring to that author has proposed a literature review of maximum power point tracking for PV system. MPPT used generally for the selection of the maximum power from the PV module and turning that power to the load where The converter acts an interface between the PV module and the load as shown in Fig.…”

Section: Pv Systemsmentioning

confidence: 99%

Challenges of Smart Integration Systems: A Review

Mourad¹,

Elbaset²,

Ziedan³

2017

IJEEE

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Recently the important for Distribution Generation (DG) take large scale for researchers. But future electricity demand will grow. This requires attention by implementation smart integration now. This aim to the intelligent integration where grid-connected PV systems, wind energy systems that are planned for a dynamic interface with the grid in the context of so called smart integration between the distribution generation resources and the power generation system. The development in smart integration will solve more problems for network such as: (1) improve the efficiency in production, (2) consumption of electricity, and (3) increase reliability of integration of renewable energy into the grid. This requires control strategies, metering and monitor technology. It's aim to automation processes. The renewable Distribution Generation (DG) such as solar photovoltaic (PV) and wind has received a great attention. This paper aimed to wide survey of researchers in the field of the micro-grid until this moment down to the smart integration.  Index Terms-renewable energy, PV systems, micro-grids, storage systems, integration of PV with grid Adel A. Elbaset Mohammed was born in Nag Hamadi, Qena-Egypt, on October 24, 1971. He received his B.S., M.Sc., and Ph.D. from

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A Comprehensive Survey of Maximum Power Tracker Techniques for Photovoltaic System

Cited by 2 publications

References 0 publications

Research on the voltage prediction of unmanned aerial vehicle photovoltaic modules based on new combination optimization algorithm

Research on the voltage prediction of unmanned aerial vehicle photovoltaic modules based on new combination optimization algorithm

Challenges of Smart Integration Systems: A Review

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