Adaptive Least Mean Square Controller for Power Quality Enhancement in Solar Photovoltaic System
The objective of the proposed work is to develop a Maximum Power Point Tracking (MPPT) controller and inverter controller by applying the adaptive least mean square (LMS) algorithm to control the total harmonics distortion of a solar photovoltaic system. The advantage of the adaptive LMS algorithm i...
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MDPI AG
2022-11-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/23/8909 |
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| author | Nalini Karchi Deepak Kulkarni Rocío Pérez de Prado Parameshachari Bidare Divakarachari Sujata N. Patil Veena Desai |
| author_facet | Nalini Karchi Deepak Kulkarni Rocío Pérez de Prado Parameshachari Bidare Divakarachari Sujata N. Patil Veena Desai |
| author_sort | Nalini Karchi |
| collection | DOAJ |
| description | The objective of the proposed work is to develop a Maximum Power Point Tracking (MPPT) controller and inverter controller by applying the adaptive least mean square (LMS) algorithm to control the total harmonics distortion of a solar photovoltaic system. The advantage of the adaptive LMS algorithm is given by its simplicity and reduced required computational time. The adaptive LMS algorithm is applied to modify the Perturb and Observe (P&O), MPPT controller. In this controller, the adaptive LMS algorithm is used to predict solar photovoltaic power. The adaptive LMS maximum power point tracking controller gives better optimal solutions with less steady error 0.7% (6 watts) and 0% peak overshot in power with the tradeoff being more settling time at 0.33 s. The development of the inverter control law is performed using the d-q frame theory. This helps to reduce the number of equations to build a control law. The load current, grid current and grid voltage are sensed and transformed into d and q components. This adaptive LMS control law is used to extract the reference grid currents and, later, to compare them with the actual grid currents. The result of this comparison is used to generate the switching gate pulses for the inverter switches. The proposed controllers are developed and implemented with a solar PV system in MATLAB Simulink. The total harmonics distortion in grid and load current (3.25% and 7%) and voltage (0%) is investigated under linear and non-linear load conditions with changes in solar irradiations. The analysis is performed by selecting step incremental values and sampling time. |
| first_indexed | 2024-03-09T17:49:00Z |
| format | Article |
| id | doaj.art-01ef03332bb7408398fde7ea60c0bd0b |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T17:49:00Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-01ef03332bb7408398fde7ea60c0bd0b2023-11-24T10:52:16ZengMDPI AGEnergies1996-10732022-11-011523890910.3390/en15238909Adaptive Least Mean Square Controller for Power Quality Enhancement in Solar Photovoltaic SystemNalini Karchi0Deepak Kulkarni1Rocío Pérez de Prado2Parameshachari Bidare Divakarachari3Sujata N. Patil4Veena Desai5Department of Electrical and Electronics Engineering, Gogte Institute of Technology, Belagavi 590006, IndiaDepartment of Electrical and Electronics Engineering, Gogte Institute of Technology, Belagavi 590006, IndiaTelecommunication Engineering Department, University of Jaén, 23700 Jaén, SpainDepartment of Electronics and Communication Engineering, Nitte Meenakshi Institute of Technology, Bangalore 560064, IndiaDepartment of Electronics & Communication Engineering, KLE Dr. M.S. Sheshgiri College of Engineering & Technology, Belagavi 590008, IndiaDepartment of Electronics and Communication Engineering, Gogte Institute of Technology, Belagavi 590006, IndiaThe objective of the proposed work is to develop a Maximum Power Point Tracking (MPPT) controller and inverter controller by applying the adaptive least mean square (LMS) algorithm to control the total harmonics distortion of a solar photovoltaic system. The advantage of the adaptive LMS algorithm is given by its simplicity and reduced required computational time. The adaptive LMS algorithm is applied to modify the Perturb and Observe (P&O), MPPT controller. In this controller, the adaptive LMS algorithm is used to predict solar photovoltaic power. The adaptive LMS maximum power point tracking controller gives better optimal solutions with less steady error 0.7% (6 watts) and 0% peak overshot in power with the tradeoff being more settling time at 0.33 s. The development of the inverter control law is performed using the d-q frame theory. This helps to reduce the number of equations to build a control law. The load current, grid current and grid voltage are sensed and transformed into d and q components. This adaptive LMS control law is used to extract the reference grid currents and, later, to compare them with the actual grid currents. The result of this comparison is used to generate the switching gate pulses for the inverter switches. The proposed controllers are developed and implemented with a solar PV system in MATLAB Simulink. The total harmonics distortion in grid and load current (3.25% and 7%) and voltage (0%) is investigated under linear and non-linear load conditions with changes in solar irradiations. The analysis is performed by selecting step incremental values and sampling time.https://www.mdpi.com/1996-1073/15/23/8909adaptive control algorithminverter controllerleast mean squaremaximum power point trackingphotovoltaic systempower quality issues |
| spellingShingle | Nalini Karchi Deepak Kulkarni Rocío Pérez de Prado Parameshachari Bidare Divakarachari Sujata N. Patil Veena Desai Adaptive Least Mean Square Controller for Power Quality Enhancement in Solar Photovoltaic System Energies adaptive control algorithm inverter controller least mean square maximum power point tracking photovoltaic system power quality issues |
| title | Adaptive Least Mean Square Controller for Power Quality Enhancement in Solar Photovoltaic System |
| title_full | Adaptive Least Mean Square Controller for Power Quality Enhancement in Solar Photovoltaic System |
| title_fullStr | Adaptive Least Mean Square Controller for Power Quality Enhancement in Solar Photovoltaic System |
| title_full_unstemmed | Adaptive Least Mean Square Controller for Power Quality Enhancement in Solar Photovoltaic System |
| title_short | Adaptive Least Mean Square Controller for Power Quality Enhancement in Solar Photovoltaic System |
| title_sort | adaptive least mean square controller for power quality enhancement in solar photovoltaic system |
| topic | adaptive control algorithm inverter controller least mean square maximum power point tracking photovoltaic system power quality issues |
| url | https://www.mdpi.com/1996-1073/15/23/8909 |
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