Global Maximum Power Point Tracking for Photovoltaic Systems Using Hybrid Secant and Binary Search Algorithms

Anusha Kumaresan, Glen G. Farivar, Hossein Dehghani Tafti, Neha Beniwal, Naga Brahmendra Yadav Gorla, Josep Pou

Research output: Chapter in Book/Conference paperConference paperpeer-review

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)9781728193878
DOIs
Publication statusPublished - 2022
Event2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 - Detroit, United States
Duration: 9 Oct 202213 Oct 2022

Conference

Conference2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Country/TerritoryUnited States
CityDetroit
Period9/10/2213/10/22

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