Optimized Maximum Power Point Tracking for PV System Under Partial Shading Conditions

Feixuan Yang; Haimeng Wu; Xingshuo Li; Zhiwei Gao; Mohammed Alkanderi

doi:10.1109/PEAS58692.2023.10395405

Optimized Maximum Power Point Tracking for PV System Under Partial Shading Conditions

Feixuan Yang, Haimeng Wu, Xingshuo Li, Zhiwei Gao, Mohammed Alkanderi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

112 Downloads (Pure)

Abstract

Photovoltaic (PV) systems play an important role in achieving net zero energy and sustainable development, which normally require optimal maximum power point tracking (MPPT) algorithms to be effective and efficient. Due to the partial shading condition in a PV system, several local maximum power points (LMPPs) and a global maximum power point (GMPP) are created, preventing PV systems from achieving GMPP by simply using standard MPPT techniques. This research presents an improved meta-heuristic MPPT approach to compensate for the incompetency of the most modern algorithms. A hybrid MPPT approach is developed and compared with the commonly used modified Perturb and Observe (P&O) and the recent advanced Cuckoo Search (CS) approach. Furthermore, a comprehensive evaluation and comparison is conducted to validate the performance of the proposed MPPT techniques. The results indicate that the proposed enhanced MPPT algorithm can mitigate the adverse trade-offs of the existing approaches with parameter optimization for tracking speed and steady-state oscillations while resolving the GMPP location under partially shaded PV conditions.

Original language	English
Title of host publication	023 IEEE 2nd International Power Electronics and Application Symposium (PEAS)
Place of Publication	Piscataway, NJ, USA
Publisher	IEEE
Pages	697-703
Number of pages	7
ISBN (Electronic)	9798350313765
ISBN (Print)	9798350313772
DOIs	https://doi.org/10.1109/PEAS58692.2023.10395405
Publication status	Published - 10 Nov 2023
Event	2023 IEEE 2nd International Power Electronics and Application Symposium (PEAS) - Guanzhou, Guanzhou, China Duration: 10 Nov 2023 → 13 Nov 2023 http://peas.cpss.org.cn/

Conference

Conference	2023 IEEE 2nd International Power Electronics and Application Symposium (PEAS)
Abbreviated title	IEEE PEAS 2023
Country/Territory	China
City	Guanzhou
Period	10/11/23 → 13/11/23
Internet address	http://peas.cpss.org.cn/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

photovoltaic
maximum power point tracking (MPPT)
global maximum power point (GMPP)
hybrid
Optimization
partial shading condition

Access to Document

10.1109/PEAS58692.2023.10395405

Optimized Maximum Power Point Tracking for PV System Under Partial Shading ConditionsAccepted author manuscript, 2 MB

Cite this

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title = "Optimized Maximum Power Point Tracking for PV System Under Partial Shading Conditions",

abstract = "Photovoltaic (PV) systems play an important role in achieving net zero energy and sustainable development, which normally require optimal maximum power point tracking (MPPT) algorithms to be effective and efficient. Due to the partial shading condition in a PV system, several local maximum power points (LMPPs) and a global maximum power point (GMPP) are created, preventing PV systems from achieving GMPP by simply using standard MPPT techniques. This research presents an improved meta-heuristic MPPT approach to compensate for the incompetency of the most modern algorithms. A hybrid MPPT approach is developed and compared with the commonly used modified Perturb and Observe (P\&O) and the recent advanced Cuckoo Search (CS) approach. Furthermore, a comprehensive evaluation and comparison is conducted to validate the performance of the proposed MPPT techniques. The results indicate that the proposed enhanced MPPT algorithm can mitigate the adverse trade-offs of the existing approaches with parameter optimization for tracking speed and steady-state oscillations while resolving the GMPP location under partially shaded PV conditions.",

keywords = "photovoltaic, maximum power point tracking (MPPT), global maximum power point (GMPP), hybrid, Optimization, partial shading condition",

author = "Feixuan Yang and Haimeng Wu and Xingshuo Li and Zhiwei Gao and Mohammed Alkanderi",

year = "2023",

month = nov,

day = "10",

doi = "10.1109/PEAS58692.2023.10395405",

language = "English",

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pages = "697--703",

booktitle = "023 IEEE 2nd International Power Electronics and Application Symposium (PEAS)",

publisher = "IEEE",

address = "United States",

note = "2023 IEEE 2nd International Power Electronics and Application Symposium (PEAS), IEEE PEAS 2023 ; Conference date: 10-11-2023 Through 13-11-2023",

url = "http://peas.cpss.org.cn/",

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Yang, F , Wu, H, Li, X, Gao, Z & Alkanderi, M 2023, Optimized Maximum Power Point Tracking for PV System Under Partial Shading Conditions. in 023 IEEE 2nd International Power Electronics and Application Symposium (PEAS). IEEE, Piscataway, NJ, USA, pp. 697-703, 2023 IEEE 2nd International Power Electronics and Application Symposium (PEAS), Guanzhou, China, 10/11/23. https://doi.org/10.1109/PEAS58692.2023.10395405

TY - GEN

T1 - Optimized Maximum Power Point Tracking for PV System Under Partial Shading Conditions

AU - Yang, Feixuan

AU - Wu, Haimeng

AU - Li, Xingshuo

AU - Gao, Zhiwei

AU - Alkanderi, Mohammed

PY - 2023/11/10

Y1 - 2023/11/10

N2 - Photovoltaic (PV) systems play an important role in achieving net zero energy and sustainable development, which normally require optimal maximum power point tracking (MPPT) algorithms to be effective and efficient. Due to the partial shading condition in a PV system, several local maximum power points (LMPPs) and a global maximum power point (GMPP) are created, preventing PV systems from achieving GMPP by simply using standard MPPT techniques. This research presents an improved meta-heuristic MPPT approach to compensate for the incompetency of the most modern algorithms. A hybrid MPPT approach is developed and compared with the commonly used modified Perturb and Observe (P&O) and the recent advanced Cuckoo Search (CS) approach. Furthermore, a comprehensive evaluation and comparison is conducted to validate the performance of the proposed MPPT techniques. The results indicate that the proposed enhanced MPPT algorithm can mitigate the adverse trade-offs of the existing approaches with parameter optimization for tracking speed and steady-state oscillations while resolving the GMPP location under partially shaded PV conditions.

AB - Photovoltaic (PV) systems play an important role in achieving net zero energy and sustainable development, which normally require optimal maximum power point tracking (MPPT) algorithms to be effective and efficient. Due to the partial shading condition in a PV system, several local maximum power points (LMPPs) and a global maximum power point (GMPP) are created, preventing PV systems from achieving GMPP by simply using standard MPPT techniques. This research presents an improved meta-heuristic MPPT approach to compensate for the incompetency of the most modern algorithms. A hybrid MPPT approach is developed and compared with the commonly used modified Perturb and Observe (P&O) and the recent advanced Cuckoo Search (CS) approach. Furthermore, a comprehensive evaluation and comparison is conducted to validate the performance of the proposed MPPT techniques. The results indicate that the proposed enhanced MPPT algorithm can mitigate the adverse trade-offs of the existing approaches with parameter optimization for tracking speed and steady-state oscillations while resolving the GMPP location under partially shaded PV conditions.

KW - photovoltaic

KW - maximum power point tracking (MPPT)

KW - global maximum power point (GMPP)

KW - hybrid

KW - Optimization

KW - partial shading condition

UR - https://www.scopus.com/pages/publications/85187261483

U2 - 10.1109/PEAS58692.2023.10395405

DO - 10.1109/PEAS58692.2023.10395405

M3 - Conference contribution

SN - 9798350313772

SP - 697

EP - 703

BT - 023 IEEE 2nd International Power Electronics and Application Symposium (PEAS)

PB - IEEE

CY - Piscataway, NJ, USA

T2 - 2023 IEEE 2nd International Power Electronics and Application Symposium (PEAS)

Y2 - 10 November 2023 through 13 November 2023

ER -

Optimized Maximum Power Point Tracking for PV System Under Partial Shading Conditions

Abstract

Conference

UN SDGs

Keywords

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