A Comparative Analysis of Maximum Power Point Techniques for Solar Photovoltaic Systems
The characteristics of a PV (photovoltaic) module is non-linear and vary with nature. The tracking of maximum power point (MPP) at various atmospheric conditions is essential for the reliable operation of solar-integrated power generation units. This paper compares the most widely used maximum power...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/15/22/8776 |
| _version_ | 1797465341119430656 |
|---|---|
| author | Ashwin Kumar Devarakonda Natarajan Karuppiah Tamilselvi Selvaraj Praveen Kumar Balachandran Ravivarman Shanmugasundaram Tomonobu Senjyu |
| author_facet | Ashwin Kumar Devarakonda Natarajan Karuppiah Tamilselvi Selvaraj Praveen Kumar Balachandran Ravivarman Shanmugasundaram Tomonobu Senjyu |
| author_sort | Ashwin Kumar Devarakonda |
| collection | DOAJ |
| description | The characteristics of a PV (photovoltaic) module is non-linear and vary with nature. The tracking of maximum power point (MPP) at various atmospheric conditions is essential for the reliable operation of solar-integrated power generation units. This paper compares the most widely used maximum power point tracking (MPPT) techniques such as the perturb and observe method (P&O), incremental conductance method (INC), fuzzy logic controller method (FLC), neural network (NN) model, and adaptive neuro-fuzzy inference system method (ANFIS) with the modern approach of the hybrid method (neural network + P&O) for PV systems. The hybrid method combines the strength of the neural network and P&O in a single framework. The PV system is composed of a PV panel, converter, MPPT unit, and load modelled using MATLAB/Simulink. These methods differ in their characteristics such as convergence speed, ease of implementation, sensors used, cost, and range of efficiencies. Based on all these, performances are evaluated. In this analysis, the drawbacks of the methods are studied, and wastage of the panel’s available output energy is observed. The hybrid technique concedes a spontaneous recovery during dynamic changes in environmental conditions. The simulation results illustrate the improvements obtained by the hybrid method in comparison to other techniques. |
| first_indexed | 2024-03-09T18:20:11Z |
| format | Article |
| id | doaj.art-03202ebe805d4ad5af70afc6d73078e6 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T18:20:11Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-03202ebe805d4ad5af70afc6d73078e62023-11-24T08:18:24ZengMDPI AGEnergies1996-10732022-11-011522877610.3390/en15228776A Comparative Analysis of Maximum Power Point Techniques for Solar Photovoltaic SystemsAshwin Kumar Devarakonda0Natarajan Karuppiah1Tamilselvi Selvaraj2Praveen Kumar Balachandran3Ravivarman Shanmugasundaram4Tomonobu Senjyu5Department of EEE, Vardhaman College of Engineering, Hyderabad 501218, Telangana, IndiaDepartment of EEE, Vardhaman College of Engineering, Hyderabad 501218, Telangana, IndiaDepartment of EEE, Sri Sivasubramaniya Nadar College of Engineering, Chennai 603110, Tamil Nadu, IndiaDepartment of EEE, Vardhaman College of Engineering, Hyderabad 501218, Telangana, IndiaDepartment of EEE, Vardhaman College of Engineering, Hyderabad 501218, Telangana, IndiaFaculty of Engineering, University of the Ryukyus, Okinawa 903-0213, JapanThe characteristics of a PV (photovoltaic) module is non-linear and vary with nature. The tracking of maximum power point (MPP) at various atmospheric conditions is essential for the reliable operation of solar-integrated power generation units. This paper compares the most widely used maximum power point tracking (MPPT) techniques such as the perturb and observe method (P&O), incremental conductance method (INC), fuzzy logic controller method (FLC), neural network (NN) model, and adaptive neuro-fuzzy inference system method (ANFIS) with the modern approach of the hybrid method (neural network + P&O) for PV systems. The hybrid method combines the strength of the neural network and P&O in a single framework. The PV system is composed of a PV panel, converter, MPPT unit, and load modelled using MATLAB/Simulink. These methods differ in their characteristics such as convergence speed, ease of implementation, sensors used, cost, and range of efficiencies. Based on all these, performances are evaluated. In this analysis, the drawbacks of the methods are studied, and wastage of the panel’s available output energy is observed. The hybrid technique concedes a spontaneous recovery during dynamic changes in environmental conditions. The simulation results illustrate the improvements obtained by the hybrid method in comparison to other techniques.https://www.mdpi.com/1996-1073/15/22/8776solar photovoltaic systemsmaximum power point trackingMPP algorithmsP&Oincremental conductancefuzzy logic control |
| spellingShingle | Ashwin Kumar Devarakonda Natarajan Karuppiah Tamilselvi Selvaraj Praveen Kumar Balachandran Ravivarman Shanmugasundaram Tomonobu Senjyu A Comparative Analysis of Maximum Power Point Techniques for Solar Photovoltaic Systems Energies solar photovoltaic systems maximum power point tracking MPP algorithms P&O incremental conductance fuzzy logic control |
| title | A Comparative Analysis of Maximum Power Point Techniques for Solar Photovoltaic Systems |
| title_full | A Comparative Analysis of Maximum Power Point Techniques for Solar Photovoltaic Systems |
| title_fullStr | A Comparative Analysis of Maximum Power Point Techniques for Solar Photovoltaic Systems |
| title_full_unstemmed | A Comparative Analysis of Maximum Power Point Techniques for Solar Photovoltaic Systems |
| title_short | A Comparative Analysis of Maximum Power Point Techniques for Solar Photovoltaic Systems |
| title_sort | comparative analysis of maximum power point techniques for solar photovoltaic systems |
| topic | solar photovoltaic systems maximum power point tracking MPP algorithms P&O incremental conductance fuzzy logic control |
| url | https://www.mdpi.com/1996-1073/15/22/8776 |
| work_keys_str_mv | AT ashwinkumardevarakonda acomparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT natarajankaruppiah acomparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT tamilselviselvaraj acomparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT praveenkumarbalachandran acomparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT ravivarmanshanmugasundaram acomparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT tomonobusenjyu acomparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT ashwinkumardevarakonda comparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT natarajankaruppiah comparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT tamilselviselvaraj comparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT praveenkumarbalachandran comparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT ravivarmanshanmugasundaram comparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems AT tomonobusenjyu comparativeanalysisofmaximumpowerpointtechniquesforsolarphotovoltaicsystems |