TY - GEN
T1 - PV Maximum Power-Point Tracking by Using Artificial Neural Network
AU - Shoffiana, Nur Alfiani
AU - Suyanto,
AU - Abadi, Imam
AU - Pertiwi, Nabilah Kartika
AU - Damayanti, Ayu Anisa
AU - Hartati, Ayu Dian
AU - Susanti, Mia Dwi
AU - Stendafity, Selfi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The utilization of solar panels as an effort to implement new and renewable energy still has challenges in optimizing the performance of solar panels to produce electrical power efficiently. Therefore, a careful planning and operational process is needed to maximize the performance of solar panels. One of the important steps to plan carefully the process of installing solar panels is to estimate the production of electrical power generated by solar panels. This research was conducted to design a maximum voltage estimation system on solar panels by considering solar radiation and air temperature. The Mean Squared Error (MSE) parameter is used as a performance parameter of the artificial neural network used. The results showed a significant relationship between solar radiation, air temperature and voltage on solar panels made from polycrystalline. Testing and evaluation of the estimation system is done using independent data that has never been seen before. The MSE result in the test is 9.9602e-12 which has met the MSE target set in this study.
AB - The utilization of solar panels as an effort to implement new and renewable energy still has challenges in optimizing the performance of solar panels to produce electrical power efficiently. Therefore, a careful planning and operational process is needed to maximize the performance of solar panels. One of the important steps to plan carefully the process of installing solar panels is to estimate the production of electrical power generated by solar panels. This research was conducted to design a maximum voltage estimation system on solar panels by considering solar radiation and air temperature. The Mean Squared Error (MSE) parameter is used as a performance parameter of the artificial neural network used. The results showed a significant relationship between solar radiation, air temperature and voltage on solar panels made from polycrystalline. Testing and evaluation of the estimation system is done using independent data that has never been seen before. The MSE result in the test is 9.9602e-12 which has met the MSE target set in this study.
KW - Maximum Voltage
KW - Mean Squared Error (MSE)
KW - Solar Panel
UR - http://www.scopus.com/inward/record.url?scp=85186536615&partnerID=8YFLogxK
U2 - 10.1109/ICAMIMIA60881.2023.10427794
DO - 10.1109/ICAMIMIA60881.2023.10427794
M3 - Conference contribution
AN - SCOPUS:85186536615
T3 - 2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Proceedings
SP - 859
EP - 863
BT - 2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023
Y2 - 14 November 2023 through 15 November 2023
ER -
