A Real-time Deterministic Peak Hopping Maximum Power Point Tracking Algorithm for Complex Partial Shading Condition
Conventional perturb and observe (P&O) algorithm fails to track global maximum power point (GMPP) under complex partial shading conditions (PSC). While many of the latest maximum power point tracking (MPPT) algorithms are designed to handle simpler PSCs with fewer peaks, their capability to hand...
Saved in:
Published in | IEEE access Vol. 12; p. 1 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Piscataway
IEEE
01.01.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Conventional perturb and observe (P&O) algorithm fails to track global maximum power point (GMPP) under complex partial shading conditions (PSC). While many of the latest maximum power point tracking (MPPT) algorithms are designed to handle simpler PSCs with fewer peaks, their capability to handle highly complex PSCs remains uncertain. This study presented more practical, challenging, and complex PSCs that have over five peaks and extremely close peak values. A new deterministic peak hopping (PH)-based MPPT algorithm with simple mechanisms is proposed to address these complex PSCs. An agent is utilized to scan and hop between the lower and higher duty cycle regions of P-V curve with optimum step size, thereby effectively narrowing down the tracking region, moving towards the GMPP. Additionally, the proposed algorithm utilizes an adjustable sampling time during scanning and hopping process to accelerate the convergence. Extensive simulation studies have revealed the effectiveness of the proposed algorithm in tracking GMPP. Moreover, the proposed algorithm outperforms five of the latest MPPT algorithms. In experimental setup, the proposed algorithm is successfully implemented into real-time TI C2000 microcontroller and performed robustly using ITECH IT6012C-800-40 PV simulator, achieving tracking time shorter than 0.83s and tracking accuracy over 98.70%. |
---|---|
ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2024.3380844 |