TY - JOUR
T1 - Scaled Conjugate Gradient Artificial Neural Network-Based Ripple Current Correlation MPPT Algorithms for PV System
AU - Noman, Abdullah M.
AU - Khan, Hamed
AU - Sher, Hadeed Ahmed
AU - Almutairi, Sulaiman Z.
AU - Alqahtani, Mohammed H.
AU - Aljumah, Ali S.
N1 - Publisher Copyright:
© 2023 Abdullah M. Noman et al.
PY - 2023
Y1 - 2023
N2 - This article proposes a hybrid scheme of maximum power point tracking (MPPT) based on artificial neural network (ANN) and ripple current correlation (RCC). ANN model is established using the data generated through RCC MPPT. Scaled conjugate gradient ANN is applied to gauge the performance improvement. The proposed scheme is validated through simulations. For this, the proposed system is applied to three different environmental scenarios which are standard testing condition of a PV module, under variable irradiance condition, and variable temperature condition. It is established that the proposed system is well capable of tracking the maximum power point under various test conditions.
AB - This article proposes a hybrid scheme of maximum power point tracking (MPPT) based on artificial neural network (ANN) and ripple current correlation (RCC). ANN model is established using the data generated through RCC MPPT. Scaled conjugate gradient ANN is applied to gauge the performance improvement. The proposed scheme is validated through simulations. For this, the proposed system is applied to three different environmental scenarios which are standard testing condition of a PV module, under variable irradiance condition, and variable temperature condition. It is established that the proposed system is well capable of tracking the maximum power point under various test conditions.
UR - http://www.scopus.com/inward/record.url?scp=85164224992&partnerID=8YFLogxK
U2 - 10.1155/2023/8891052
DO - 10.1155/2023/8891052
M3 - Article
AN - SCOPUS:85164224992
SN - 1110-662X
VL - 2023
JO - International Journal of Photoenergy
JF - International Journal of Photoenergy
M1 - 8891052
ER -
