TY - GEN
T1 - Global Maximum Power Point Tracking for Photovoltaic Systems Using Hybrid Secant and Binary Search Algorithms
AU - Kumaresan, Anusha
AU - Farivar, Glen G.
AU - Tafti, Hossein Dehghani
AU - Beniwal, Neha
AU - Gorla, Naga Brahmendra Yadav
AU - Pou, Josep
N1 - Funding Information:
VI. ACKNOWLEDGMENTS This work was supported by the National Research Foundation of Singapore under “Distributed Energy Resource Management Systems (DERMS) for Energy Grid 2.0” project. This work was also supported by the Office of Naval Research U.S. under DUNS Code: 595886219.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Global maximum power point tracking (GMPPT) algorithms are employed to extract the maximum available power from the photovoltaic (PV) arrays during partial shading conditions. However, the available GMPPT algorithms in the literature have disadvantages such as low convergence rate and requirement to scan for the local peaks. To overcome these drawbacks, this paper presents a fast and simple hybrid GMPPT algorithm, which combines the advantages of the binary search and the secant algorithms. The binary search algorithm is used for the global maximum power point (GMPP) reference generation and the secant algorithm is applied for tracking the generated power reference. The superlinear convergence rate of the secant algorithm and the logarithmic convergence rate of the binary search algorithm aid in fast convergence to the GMPP. The performance of the proposed hybrid GMPPT algorithm is validated through simulations in MATLAB-Simulink and also compared with a conventional GMPPT algorithm.
AB - Global maximum power point tracking (GMPPT) algorithms are employed to extract the maximum available power from the photovoltaic (PV) arrays during partial shading conditions. However, the available GMPPT algorithms in the literature have disadvantages such as low convergence rate and requirement to scan for the local peaks. To overcome these drawbacks, this paper presents a fast and simple hybrid GMPPT algorithm, which combines the advantages of the binary search and the secant algorithms. The binary search algorithm is used for the global maximum power point (GMPP) reference generation and the secant algorithm is applied for tracking the generated power reference. The superlinear convergence rate of the secant algorithm and the logarithmic convergence rate of the binary search algorithm aid in fast convergence to the GMPP. The performance of the proposed hybrid GMPPT algorithm is validated through simulations in MATLAB-Simulink and also compared with a conventional GMPPT algorithm.
KW - Active power control
KW - binary search algorithm
KW - maximum power point tracking
KW - photovoltaic (PV) systems
KW - secant algorithm
UR - http://www.scopus.com/inward/record.url?scp=85144047424&partnerID=8YFLogxK
U2 - 10.1109/ECCE50734.2022.9948026
DO - 10.1109/ECCE50734.2022.9948026
M3 - Conference paper
AN - SCOPUS:85144047424
BT - 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
PB - IEEE, Institute of Electrical and Electronics Engineers
CY - USA
T2 - 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Y2 - 9 October 2022 through 13 October 2022
ER -