Analysis of photovoltaic array maximum power point tracking under uniform environment and partial shading condition: A review

With the expansion of the scale of application of photovoltaic (PV) power generation, PV maximum power point tracking (MPPT) technology has been transformed from uniform environmental conditions (UEC) to partial shading conditions (PSC), but there are certain limitations in the application of existi...

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Vydáno v:Energy reports Ročník 8; s. 13235 - 13252
Hlavní autoři: Li, Jianlin, Wu, Yiwen, Ma, Suliang, Chen, Mingxuan, Zhang, Baoping, Jiang, Bing
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.11.2022
Elsevier
Témata:
Maximum power-point tracking
Partially shaded conditions
Photovoltaic mathematical model
Swarm intelligence optimization algorithm
Uniform environment condition
Photovoltaic mathematical model
Uniform environment condition
Maximum power-point tracking
Swarm intelligence optimization algorithm
Partially shaded conditions
ISSN:2352-4847, 2352-4847
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Abstract With the expansion of the scale of application of photovoltaic (PV) power generation, PV maximum power point tracking (MPPT) technology has been transformed from uniform environmental conditions (UEC) to partial shading conditions (PSC), but there are certain limitations in the application of existing technologies under PSC. At present, a large number of several different PV MPPT algorithms have been proposed. In the research on MPPT technology under UEC, the MPPT technology based on the output characteristics of PV cells is used and the MPPT tracking speed has reached 20 times, in another improvement, the MPPT technology based on PV cell model is used, and the MPPT tracking accuracy has reached 99.4428%. In the process of MPPT technology transformation, there is a lack of sufficient comparative analysis and systematic review of these methods. This paper focuses on the tracking problem of the Voltage–Power (U–P) single-peak curve under the UEC to the U–P​ multi-peak curve under the partial shading conditions (PSC), and discuss four key issues in the development of PV MPPT research: (1) Under UEC, the performance of MPPT algorithms based on PV output characteristics and PV cell model; (2) The failure phenomenon when traditional MPPT technology is applied under PSC; (3) Under the PSC, the application process of the traditional methods and the swarm intelligence optimization algorithm (SIOA); (4) The bottlenecks faced by SIOA applications under PSC and the analysis of solutions. Through the analysis and comparison presented in this study, researchers can comprehensively understand the development and the important changes brought by PSC to MPPT technology. This could lead to exploration and research into the applications of SIOA in MPPT technology under PSC. The relevant conclusions will provide important directions for future research in the field of MPPT under PSC. •Under the uniform environmental conditions, the paper divides the traditional MPPT technology into two categories, the MPPT technology based on photovoltaic cell output characteristics and the MPPT technology based on photovoltaic cell model driving, discusses the implementation ideas and improvements of typical methods, compares their tracking performance in detail, and provide new ideas for MPPT technology.•The characteristics, advantages and disadvantages of the existing technology are compared from the two aspects of uniform environmental conditions and partially shaded conditions, the reasons for the failure of traditional algorithms under partially shaded conditions are analyzed in detail, and the improvement methods of traditional methods under partially shaded conditions are proposed.•For the first time, the bottleneck of the application of swarm intelligence optimization algorithm in partially shaded conditions is comprehensively analyzed from three aspects: start-up condition, dynamic tracking performance and cut-off condition. The work in this paper can provide a new way for the development of MPPT technology in the future.
AbstractList With the expansion of the scale of application of photovoltaic (PV) power generation, PV maximum power point tracking (MPPT) technology has been transformed from uniform environmental conditions (UEC) to partial shading conditions (PSC), but there are certain limitations in the application of existing technologies under PSC. At present, a large number of several different PV MPPT algorithms have been proposed. In the research on MPPT technology under UEC, the MPPT technology based on the output characteristics of PV cells is used and the MPPT tracking speed has reached 20 times, in another improvement, the MPPT technology based on PV cell model is used, and the MPPT tracking accuracy has reached 99.4428%. In the process of MPPT technology transformation, there is a lack of sufficient comparative analysis and systematic review of these methods. This paper focuses on the tracking problem of the Voltage–Power (U–P) single-peak curve under the UEC to the U–P​ multi-peak curve under the partial shading conditions (PSC), and discuss four key issues in the development of PV MPPT research: (1) Under UEC, the performance of MPPT algorithms based on PV output characteristics and PV cell model; (2) The failure phenomenon when traditional MPPT technology is applied under PSC; (3) Under the PSC, the application process of the traditional methods and the swarm intelligence optimization algorithm (SIOA); (4) The bottlenecks faced by SIOA applications under PSC and the analysis of solutions. Through the analysis and comparison presented in this study, researchers can comprehensively understand the development and the important changes brought by PSC to MPPT technology. This could lead to exploration and research into the applications of SIOA in MPPT technology under PSC. The relevant conclusions will provide important directions for future research in the field of MPPT under PSC. •Under the uniform environmental conditions, the paper divides the traditional MPPT technology into two categories, the MPPT technology based on photovoltaic cell output characteristics and the MPPT technology based on photovoltaic cell model driving, discusses the implementation ideas and improvements of typical methods, compares their tracking performance in detail, and provide new ideas for MPPT technology.•The characteristics, advantages and disadvantages of the existing technology are compared from the two aspects of uniform environmental conditions and partially shaded conditions, the reasons for the failure of traditional algorithms under partially shaded conditions are analyzed in detail, and the improvement methods of traditional methods under partially shaded conditions are proposed.•For the first time, the bottleneck of the application of swarm intelligence optimization algorithm in partially shaded conditions is comprehensively analyzed from three aspects: start-up condition, dynamic tracking performance and cut-off condition. The work in this paper can provide a new way for the development of MPPT technology in the future.
With the expansion of the scale of application of photovoltaic (PV) power generation, PV maximum power point tracking (MPPT) technology has been transformed from uniform environmental conditions (UEC) to partial shading conditions (PSC), but there are certain limitations in the application of existing technologies under PSC. At present, a large number of several different PV MPPT algorithms have been proposed. In the research on MPPT technology under UEC, the MPPT technology based on the output characteristics of PV cells is used and the MPPT tracking speed has reached 20 times, in another improvement, the MPPT technology based on PV cell model is used, and the MPPT tracking accuracy has reached 99.4428%. In the process of MPPT technology transformation, there is a lack of sufficient comparative analysis and systematic review of these methods. This paper focuses on the tracking problem of the Voltage–Power (U–P) single-peak curve under the UEC to the U–P​ multi-peak curve under the partial shading conditions (PSC), and discuss four key issues in the development of PV MPPT research: (1) Under UEC, the performance of MPPT algorithms based on PV output characteristics and PV cell model; (2) The failure phenomenon when traditional MPPT technology is applied under PSC; (3) Under the PSC, the application process of the traditional methods and the swarm intelligence optimization algorithm (SIOA); (4) The bottlenecks faced by SIOA applications under PSC and the analysis of solutions. Through the analysis and comparison presented in this study, researchers can comprehensively understand the development and the important changes brought by PSC to MPPT technology. This could lead to exploration and research into the applications of SIOA in MPPT technology under PSC. The relevant conclusions will provide important directions for future research in the field of MPPT under PSC.
Author Chen, Mingxuan
Jiang, Bing
Li, Jianlin
Zhang, Baoping
Ma, Suliang
Wu, Yiwen
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Keywords Photovoltaic mathematical model
Uniform environment condition
Maximum power-point tracking
Swarm intelligence optimization algorithm
Partially shaded conditions
Language English
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Snippet With the expansion of the scale of application of photovoltaic (PV) power generation, PV maximum power point tracking (MPPT) technology has been transformed...
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SubjectTerms Maximum power-point tracking
Partially shaded conditions
Photovoltaic mathematical model
Swarm intelligence optimization algorithm
Uniform environment condition
Title Analysis of photovoltaic array maximum power point tracking under uniform environment and partial shading condition: A review
URI https://dx.doi.org/10.1016/j.egyr.2022.09.192
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