TY - JOUR
T1 - Comparative study of modern heuristic algorithms for global maximum power point tracking in photovoltaic systems under partial shading conditions
AU - Wang, Kangshi
AU - Ma, Jieming
AU - Man, Ka Lok
AU - Huang, Kaizhu
AU - Huang, Xiaowei
N1 - Publisher Copyright:
Copyright © 2022 Wang, Ma, Man, Huang and Huang.
PY - 2022/9/2
Y1 - 2022/9/2
N2 - Under partial shading conditions (PSCs), photovoltaic (PV) generation systems exhibit multiple local and a single global maximum power point. Consequently, global maximum power point tracking (GMPPT) is required to improve the performance of PV systems in such scenarios. This paper comparatively studies and evaluates the tracking performance of modern heuristic-optimization-based GMPPT techniques. Monte Carlo method is used to statistically analyze different methods. Simulation and experimental results indicate that many of the algorithms have difficulties in balancing the explorative and exploitative searching behaviors. Therefore, we propose a variable vortex search (VVS), which is capable of improving the performance of GMPPT by using a variable step size and deterministic starting points. This paper will aid researchers and practical engineers to gain a thorough understanding on how to use modern heuristic algorithms for maximum power out of PV systems. Furthermore, it offers a comprehensive guidance on how to perform efficiently GMPPT in the PV systems under PSCs.
AB - Under partial shading conditions (PSCs), photovoltaic (PV) generation systems exhibit multiple local and a single global maximum power point. Consequently, global maximum power point tracking (GMPPT) is required to improve the performance of PV systems in such scenarios. This paper comparatively studies and evaluates the tracking performance of modern heuristic-optimization-based GMPPT techniques. Monte Carlo method is used to statistically analyze different methods. Simulation and experimental results indicate that many of the algorithms have difficulties in balancing the explorative and exploitative searching behaviors. Therefore, we propose a variable vortex search (VVS), which is capable of improving the performance of GMPPT by using a variable step size and deterministic starting points. This paper will aid researchers and practical engineers to gain a thorough understanding on how to use modern heuristic algorithms for maximum power out of PV systems. Furthermore, it offers a comprehensive guidance on how to perform efficiently GMPPT in the PV systems under PSCs.
KW - global maximum power point (GMPP) tracking
KW - heuristic optimization
KW - maximum power point tracking (MPPT)
KW - partial shading condition (PSC)
KW - solar PV (SPV) systems
KW - vortex search (VS.) algorithm
UR - http://www.scopus.com/inward/record.url?scp=85138189877&partnerID=8YFLogxK
U2 - 10.3389/fenrg.2022.946864
DO - 10.3389/fenrg.2022.946864
M3 - Article
AN - SCOPUS:85138189877
SN - 2296-598X
VL - 10
JO - Frontiers in Energy Research
JF - Frontiers in Energy Research
M1 - 946864
ER -