TY - GEN
T1 - A Unified Bandgap Dependent Model for Photovoltaic Performance Analysis
AU - Mallick, Subha Prakash
AU - Dash, D. P.
AU - Lu, Tien Chang
AU - Mahato, S. S.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - The solar cell current usually depends upon carrier lifetime, diffusion length, diffusion constant, ideality factor etc. This article proposes a model that shows direct dependency of bandgap in the solar cell current equation. Hence this model is more suitable to analyze the efficiency of multi-junction solar cells in terms of corresponding material bandgaps. It also discusses how our developed model satisfies the experimental results for different single junction and multi-junction solar cells having different bandgaps. Different optimization techniques like Gauss Newton Optimization(GNO), Levenberg Marquardt Optimization(LMO), and Differential Evolution Algorithm (DEA) are used for parameter extraction and optimization. Further result analysis is done on the basis of percentage deviation and error comparison of the model with the experimental data. Complete comprehensive study leads to Differential Evolution Algorithm (DEA) as one of the best optimization technique among all with the smallest possible value of error and minimum percentage deviation.
AB - The solar cell current usually depends upon carrier lifetime, diffusion length, diffusion constant, ideality factor etc. This article proposes a model that shows direct dependency of bandgap in the solar cell current equation. Hence this model is more suitable to analyze the efficiency of multi-junction solar cells in terms of corresponding material bandgaps. It also discusses how our developed model satisfies the experimental results for different single junction and multi-junction solar cells having different bandgaps. Different optimization techniques like Gauss Newton Optimization(GNO), Levenberg Marquardt Optimization(LMO), and Differential Evolution Algorithm (DEA) are used for parameter extraction and optimization. Further result analysis is done on the basis of percentage deviation and error comparison of the model with the experimental data. Complete comprehensive study leads to Differential Evolution Algorithm (DEA) as one of the best optimization technique among all with the smallest possible value of error and minimum percentage deviation.
UR - http://www.scopus.com/inward/record.url?scp=85080134987&partnerID=8YFLogxK
U2 - 10.1109/ICCE-TW46550.2019.8991707
DO - 10.1109/ICCE-TW46550.2019.8991707
M3 - Conference contribution
AN - SCOPUS:85080134987
T3 - 2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019
BT - 2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019
Y2 - 20 May 2019 through 22 May 2019
ER -
