Volume 22, Issue 3 (JIAEEE Vol.22 No.3 2025)                   Journal of Iranian Association of Electrical and Electronics Engineers 2025, 22(3): 0-0 | Back to browse issues page

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abedini A, CHARMAHALI I, rashidi B. A novel algorithm for tracking power in solar cells based on neural network trained with multi verse optimization algorithm. Journal of Iranian Association of Electrical and Electronics Engineers 2025; 22 (3)
URL: http://jiaeee.com/article-1-1683-en.html
A novel algorithm for tracking power in solar cells based on neural network trained with multi verse optimization algorithm
Abedini Abedini * , Iman CHARMAHALI , Bahram Rashidi
brojerdi
Abstract:   (23 Views)
Solar systems need to deliver their output panel voltage to extract the maximum power that can be delivered to the load when the weather conditions change. Such energy compatibility should perform well. That is, it must be ensured that the panel's operating point is close to the maximum value. Therefore, in this article, a new method of power tracking is used, which is based on the combination of neural networks and a meta-heuristic algorithm called multi-order optimization, in order to overcome the problems of conventional methods caused by being slow to respond to temperature changes. and the radiation prevails. Therefore, it has been tried to train the weights of the neural network with a new training method based on the meta-heuristic algorithm so that it can quickly respond to these changes in case of any change in the temperature or the radiation of the controller. To show the efficiency of the proposed method, the results are compared with conventional methods and neural network whose weights are not optimized in different scenarios, which will show higher speed and provide more output power.
 
Keywords: Neural network, multi-verse optimization, maximum power point tracking
     
Type of Article: Research | Subject: Power
Received: 2023/12/23 | Accepted: 2025/03/15
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