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Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems

Cagfer Yanarates, Yidong Wang, Zhongfu Zhou Orcid Logo

IEEE Access, Volume: 9, Pages: 138468 - 138482

Swansea University Author: Zhongfu Zhou Orcid Logo

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DOI (Published version): 10.1109/access.2021.3119042

Abstract

In this paper, Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller based variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is presented. The proposed control scheme resolved the drawbacks of the conventi...

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Published in: IEEE Access
ISSN: 2169-3536
Published: Institute of Electrical and Electronics Engineers (IEEE) 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa58377
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spelling 2022-10-31T17:32:48.6421779 v2 58377 2021-10-18 Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems 614fc57cde2ee383718d4f4c462b5fba 0000-0002-0843-7253 Zhongfu Zhou Zhongfu Zhou true false 2021-10-18 EEEG In this paper, Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller based variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is presented. The proposed control scheme resolved the drawbacks of the conventional P&O MPPT method associated with the use of constant perturbation size that leads to poor transient response and high continuous steady-state oscillations. The prime objective of using the PR-P controller is to utilize inherited properties of the signal produced by the controller’s resonant path and integrate it to update the best-estimated perturbation that represents the working principle of extremum seeking control (ESC) to use in the P&O algorithm that characterizes the overall system learning-based real-time adaptive (RTA). Additionally, utilization of internal dynamics of the PR-P controller overcomes the challenges namely, complexity, computational burden, implantation cost, and slow tracking performance in association with commonly used soft computing intelligent systems and adaptive control strategies. The proposed control scheme is verified using MATLAB/Simulink by applying comparative analysis with PI-controlled conventional P&O MPPT algorithm. Moreover, the performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor board, DS2004 A/D, and CP4002 Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed five times with reduced steady-state oscillations around maximum power point (MPP) and more than 99% energy extracting efficiency. Journal Article IEEE Access 9 138468 138482 Institute of Electrical and Electronics Engineers (IEEE) 2169-3536 15 10 2021 2021-10-15 10.1109/access.2021.3119042 COLLEGE NANME Electronic and Electrical Engineering COLLEGE CODE EEEG Swansea University SU College/Department paid the OA fee 2022-10-31T17:32:48.6421779 2021-10-18T10:05:13.7691274 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering Cagfer Yanarates 1 Yidong Wang 2 Zhongfu Zhou 0000-0002-0843-7253 3 58377__21340__1661bd0bba9947449e7b58579f63d698.pdf 58377.pdf 2021-10-28T14:36:43.4555100 Output 3860010 application/pdf Version of Record true This work is licensed under a Creative Commons Attribution 4.0 License true eng https://creativecommons.org/licenses/by/4.0/
title Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems
spellingShingle Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems
Zhongfu Zhou
title_short Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems
title_full Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems
title_fullStr Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems
title_full_unstemmed Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems
title_sort Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller-Based Variable Perturbation Size Real-Time Adaptive Perturb and Observe (P&O) MPPT Algorithm for PV Systems
author_id_str_mv 614fc57cde2ee383718d4f4c462b5fba
author_id_fullname_str_mv 614fc57cde2ee383718d4f4c462b5fba_***_Zhongfu Zhou
author Zhongfu Zhou
author2 Cagfer Yanarates
Yidong Wang
Zhongfu Zhou
format Journal article
container_title IEEE Access
container_volume 9
container_start_page 138468
publishDate 2021
institution Swansea University
issn 2169-3536
doi_str_mv 10.1109/access.2021.3119042
publisher Institute of Electrical and Electronics Engineers (IEEE)
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering
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description In this paper, Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller based variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is presented. The proposed control scheme resolved the drawbacks of the conventional P&O MPPT method associated with the use of constant perturbation size that leads to poor transient response and high continuous steady-state oscillations. The prime objective of using the PR-P controller is to utilize inherited properties of the signal produced by the controller’s resonant path and integrate it to update the best-estimated perturbation that represents the working principle of extremum seeking control (ESC) to use in the P&O algorithm that characterizes the overall system learning-based real-time adaptive (RTA). Additionally, utilization of internal dynamics of the PR-P controller overcomes the challenges namely, complexity, computational burden, implantation cost, and slow tracking performance in association with commonly used soft computing intelligent systems and adaptive control strategies. The proposed control scheme is verified using MATLAB/Simulink by applying comparative analysis with PI-controlled conventional P&O MPPT algorithm. Moreover, the performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor board, DS2004 A/D, and CP4002 Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed five times with reduced steady-state oscillations around maximum power point (MPP) and more than 99% energy extracting efficiency.
published_date 2021-10-15T04:14:52Z
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