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State-of-the-art review of MPPT techniques for hybrid PV-TEG systems: modeling,methodologies,and perspectives

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State-of-the-art review of MPPT techniques for hybrid PV-TEG systems: modeling,methodologies,and perspectives

混合光伏-温差系统最大功率点跟踪技术最新综述:建模、方法和前景展望

Bo Yang1,Rui Xie1,Jinhang Duan1,Jingbo Wang2

1.Faculty of Electric Power Engineering,Kunming University of Science and Technology,650500 Kunming,P.R.China

2.Department of Electrical Engineering and Electronics,University of Liverpool,L69 3GJ Liverpool,UK

Abstract

The development of alternative renewable energy technologies is crucial for alleviating climate change and promoting energy transformation.Of the currently available technologies,solar energy has promising application prospects owing to its merits of being clean,safe,and sustainable.Solar energy is converted into electricity through photovoltaic (PV) cells; however,the overall conversion efficiency of PV modules is relatively low,and most of the captured solar energy is dissipated in the form of heat.This not only reduces the power generation efficiency of solar cells but may also have a negative impact on the electrical parameters of PV modules and the service life of PV cells.To overcome the shortcomings,an efficient approach involves combining a PV cell with a thermoelectric generator (TEG) to form hybrid PV-TEG systems,which simultaneously improve the energy conversion efficiency of the PV system by reducing the operating temperature of the PV modules and increasing the power output by utilizing the waste heat generated from the PV system to generate electricity via the TEGs.Based on a thorough examination of the literature,this study comprehensively reviews 14 maximum power point tracking(MPPT) algorithms currently applied to hybrid PV-TEG systems and classifies them into five major categories for further discussion,namely conventional,mathematics-based,metaheuristic,artificial intelligence,and other algorithms.This review aims to inspire advanced ideas and research on MPPT algorithms for hybrid PV-TEG systems.

Keywords

Photovoltaic; Thermoelectric generator; Hybrid PV-TEG; MPPT; Partial shading condition

Fig. 1 PV-TEG hybrid system topology diagram

Fig. 2 Structure of this review

Fig. 3 Relationships between the chapters in this review

Fig. 4 Review screening methods of related references: (a) review screening procedure and (b) research trend statistics based on numbers of publications per year

Fig. 5 Structure of a typical PV-TEG hybrid module

Fig. 6 A PV-TEG device with a reflective component

Fig. 7 PV battery with bypass diode: (a) with PSC and (b) under uniform condition

Fig. 8 Comparison of output characteristic curves of PV arrays under PSC and uniform condition:(a) P-V curve and (b) P-I curve

Fig. 9 Implementation process of the P&O method

Fig. 10 Comparison between P&O fixed and variable steps

Fig. 11 Execution process of the INC method

Fig. 12 A schematic diagram of the AOS principle: (a) the behavior of electrons in atoms and(b) PDF determines the distribution of the candidate solutions

Fig. 13 Optimization flowchart of AOS

Fig. 14 Searching phases of the AOA

Fig. 15 Flowchart of the AOA-based MPPT within a PV-TEG system

Fig. 16 Schematic diagram of the SQS-NN structure

Fig. 17  Flowchart of the SQS-FFNN-based MPPT of a hybrid PV-TEG system

Fig. 18 Comparison and evaluation of five types of MPPT algorithms

本文引文信息

Yang B, Xie R, Duan JH, et al. (2023) State-of-the-art review of MPPT techniques for hybrid PV-TEG systems: modeling, methodologies, and perspectives, Global Energy Interconnection, 6(5): 567-591

杨博,谢蕊,段金航等 (2023) 混合光伏-温差系统 最大功率点跟踪技术最新综述:建模、方法和前景展望. 全球能源互联网(英文), 6(5): 567-591

Biographies

Bo Yang

is a professor and Ph.D.supervisor in the School of Electric Power Engineering,Kunming University of Science and Technology,and received his Ph.D.degree from the University of Liverpool,UK,in 2015.He has published more than 150 SCI journal papers and 30 EI journal papers.His research interests include smart grid and the optimization and control of new energy systems based on artificial intelligence.

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Rui Xie

received her B.E.degree from Kunming University of Science and Technology in 2022 and is currently pursuing a master’s degree in power systems and their automation in the School of Electric Power Engineering,Kunming University of Science and Technology.Her research interests include maximum power point tracking of hybrid PVTEG systems and economic dispatch.

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Jinhang Duan

received her B.E.degree from Kunming University of Science and Technology in 2022 and is currently pursuing a master’s degree in electrical engineering in the School of Electric Power Engineering,Kunming University of Science and Technology.Her research interests include wave energy converter array layout optimization and economic dispatch.

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Jingbo Wang

received his master’s degree from Kunming University of Science and Technology in 2022,and was awarded a full scholarship by China Scholarship Council(CSC) to study for a doctoral degree at the University of Liverpool,UK,in 2022.His research interests include modeling and optimization of new energy generation systems.Corresponding author.

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