Photovoltaic Power Output Prediction using Graphical User Interface and Artificial Neural Network

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Mahadzir Cempaka Amalin; Mohamad Nor Ahmad Fateh; Jumaat Siti Amely

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Majlesi Journal of Electrical Engineering Year:2023 | Volume:17 | Issue:4 Page(s): 73-78

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

Photovoltaic Power Output Prediction using Graphical User Interface and Artificial Neural Network

Author(s)

Mahadzir Cempaka Amalin | Mohamad Nor Ahmad Fateh | Jumaat Siti Amely | Issue Writer Certificate

Keywords

Prediction

PV panel

solar output

GUI

ANN

Abstract

This paper focuses on the development of a Graphical User Interface (GUI) and Artificial Neural Network (ANN) for the Prediction of photovoltaic (PV) power output. PV power is generated based on the time, location, and surrounding climate conditions. Therefore, solar power generation Predictions using computational methods are needed since the changing weather, which will impact the output power will not generate according to its rating. The objectives of this research are to predict photovoltaic power output at Universiti Tun Hussein Onn Malaysia (UTHM), develop an ANN configuration that can perform the Prediction of solar power generation, and design GUI system that can both perform the calculations of power generation and ANN. In order to test the efficiency and reliability, MATLAB software has been used to develop the GUI and ANN, and the output is compared with the proposed mathematical equations. The real data as input data was obtained from the PV solar panel located at GSEnergy Focus Group fertigation site. The GUI with user-friendly features and ANN have been successfully designed and developed which can perform daily Prediction of solar power output. On top of that, the results have shown that the ANN Predictions are more precise to the real data than the GUI.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans