Fusion wind and solar generation prototype design with Neural Network

Wind and solar power are the most common renewable resources of energy and their usage for power generation is quickly growing all over the world. However, both wind and solar power are difficult to predict manually due to every time changes in weather condition; therefore, power output of wind and...

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Bibliographic Details
Published in:Journal of physics. Conference series 2021-08, Vol.1997 (1), p.12023
Main Authors: Al Asbahi, M M Y M, Mansor, M N, Manan, M R, Aziz, M A A, Kawi, R Md, Mohd Faudzi, F H
Format: Article
Language:English
Subjects:
Distributed generation
Neural networks
Performance measurement
Physics
Renewable resources
Solar energy
Weather
Citations: Items that this one cites
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Summary:Wind and solar power are the most common renewable resources of energy and their usage for power generation is quickly growing all over the world. However, both wind and solar power are difficult to predict manually due to every time changes in weather condition; therefore, power output of wind and solar is associated with some uncertainty. A reliable wind-solar day ahead load prediction with neural network was proposed to support a small microgrids system. All the system performance measurement such as sensitivity, specificity and accuracy give higher than 90%.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1997/1/012023