Soft computing and IoT based solar tracker

The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we propounded a solar positioning system with the use of the global positioning system (GPS) , artificial neural network (ANN) and image processing (IP)...

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Vydané v:International Journal of Power Electronics and Drive Systems Ročník 12; číslo 3; s. 1880
Hlavní autori: Kumar, Kanhaiya, Varshney, Lokesh, Ambikapathy, A., Mittal, Vrinda, Prakash, Sachin, Chandra, Prashant, Khan, Namya
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Yogyakarta IAES Institute of Advanced Engineering and Science 01.09.2021
Predmet:
Algorithms
Artificial neural networks
Azimuth
Centroids
Decision making
Error reduction
Global positioning systems
GPS
Image processing
Power gain
Soft computing
Solar energy
Sun
Tracking errors
Tracking systems
Weather
ISSN:2088-8694, 2722-256X, 2088-8694
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Abstract The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we propounded a solar positioning system with the use of the global positioning system (GPS) , artificial neural network (ANN) and image processing (IP) . The azimuth angle of the sun is evaluated using GPS which provide latitude, date, longitude and time. The image processing used to find sun image through which centroid of sun is calculated and finally by comparing the centroid of sun with GPS quadrate to achieve optimum tracking point. Weather conditions and situation observed through AI decision making with the help of IP algorithms. The presented advance adaptation is analyzed and established via experimental effects which might be made available on the memory of the cloud carrier for systematization. The proposed system improve power gain by 59.21% and 10.32% compare to stable system (SS) and two-axis solar following system (TASF) respectively. The reduced tracking error of IoT based Two-axis solar following system (IoT-TASF) reduces their azimuth angle error by 0.20 degree.
AbstractList The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we propounded a solar positioning system with the use of the global positioning system (GPS) , artificial neural network (ANN) and image processing (IP) . The azimuth angle of the sun is evaluated using GPS which provide latitude, date, longitude and time. The image processing used to find sun image through which centroid of sun is calculated and finally by comparing the centroid of sun with GPS quadrate to achieve optimum tracking point. Weather conditions and situation observed through AI decision making with the help of IP algorithms. The presented advance adaptation is analyzed and established via experimental effects which might be made available on the memory of the cloud carrier for systematization. The proposed system improve power gain by 59.21% and 10.32% compare to stable system (SS) and two-axis solar following system (TASF) respectively. The reduced tracking error of IoT based Two-axis solar following system (IoT-TASF) reduces their azimuth angle error by 0.20 degree.
Author Mittal, Vrinda
Varshney, Lokesh
Ambikapathy, A.
Prakash, Sachin
Kumar, Kanhaiya
Chandra, Prashant
Khan, Namya
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Snippet The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we...
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StartPage 1880
SubjectTerms Algorithms
Artificial neural networks
Azimuth
Centroids
Decision making
Error reduction
Global positioning systems
GPS
Image processing
Power gain
Soft computing
Solar energy
Sun
Tracking errors
Tracking systems
Weather
Title Soft computing and IoT based solar tracker
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