Dynamic Performance Improvement Using Model Reference Adaptive Control of Photovoltaic Systems under Fast-Changing Atmospheric Conditions
The effectiveness of a photovoltaic (PV) system can be increased by using maximum power point tracking (MPPT). The literature has suggested a number of methods for tracking the maximum power point (MPP). However, this number of methods most often presents a high convergence speed in reaching the MPP...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2023-01-01
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| Series: | International Journal of Photoenergy |
| Online Access: | http://dx.doi.org/10.1155/2023/5703727 |
| _version_ | 1797692149418950656 |
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| author | Yves Abessolo Mindzie Joseph Kenfack Voufo Joseph Urbain Nzotcha Dieudonné Marcel Djanssou Raphael Mbounguen |
| author_facet | Yves Abessolo Mindzie Joseph Kenfack Voufo Joseph Urbain Nzotcha Dieudonné Marcel Djanssou Raphael Mbounguen |
| author_sort | Yves Abessolo Mindzie |
| collection | DOAJ |
| description | The effectiveness of a photovoltaic (PV) system can be increased by using maximum power point tracking (MPPT). The literature has suggested a number of methods for tracking the maximum power point (MPP). However, this number of methods most often presents a high convergence speed in reaching the MPP, complexity under their implementation, power fluctuations, overshoots, and great difficulty in reaching the MPP under fast-changing atmospheric conditions, thus influencing the efficiency of PV systems. Intending to improve the performance of PV systems under rapid changes in the atmosphere, this paper proposes model reference adaptive control (MRAC) as a technique for tracking the MPP based on the employ of reference models such as optimal voltage and current at the MPP (VMPP and IMPP). The MATLAB/Simulink environment is used to produce the simulation results; the Kyocera Solar KC 130 GT module is used here as a photovoltaic power plant, connected to a boost converter, supplying a resistive load. The Lyapunov theory was used to demonstrate the stability of the system. The simulation outcomes obtained using the suggested method are compared with those obtained by techniques such as perturb and observe (P&O), incremental conductance (INC), variable step incremental conductance (VSINC), particle swarm optimization (PSO), and grey wolf optimization (GWO), thus showing a very large improvement under standard test and fast-changing atmospheric conditions of the technique proposed on the other techniques in terms of convergence speed and tracking efficiency. The simulation results prove that the suggested method has great tracking effectiveness (>99.88%), less time for convergence (<0.01 s), and simple implementation complexity under fast-changing atmospheric conditions without both transient and steady-state power oscillations, overshoots, and chattering effects, thus causing a great minimization of energy losses, and the proposed technique reaches exactly the MPP under fast-changing atmospheric conditions. |
| first_indexed | 2024-03-12T02:24:24Z |
| format | Article |
| id | doaj.art-c28c45d7737e43698ba9f2b3812a087c |
| institution | Directory Open Access Journal |
| issn | 1687-529X |
| language | English |
| last_indexed | 2024-03-12T02:24:24Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi Limited |
| record_format | Article |
| series | International Journal of Photoenergy |
| spelling | doaj.art-c28c45d7737e43698ba9f2b3812a087c2023-09-06T00:00:00ZengHindawi LimitedInternational Journal of Photoenergy1687-529X2023-01-01202310.1155/2023/5703727Dynamic Performance Improvement Using Model Reference Adaptive Control of Photovoltaic Systems under Fast-Changing Atmospheric ConditionsYves Abessolo Mindzie0Joseph Kenfack1Voufo Joseph2Urbain Nzotcha3Dieudonné Marcel Djanssou4Raphael Mbounguen5Laboratory of EnergyLaboratory of EnergyLaboratory of EnergyLaboratory of EnergyDepartment of Renewable EnergyLaboratory of EnergyThe effectiveness of a photovoltaic (PV) system can be increased by using maximum power point tracking (MPPT). The literature has suggested a number of methods for tracking the maximum power point (MPP). However, this number of methods most often presents a high convergence speed in reaching the MPP, complexity under their implementation, power fluctuations, overshoots, and great difficulty in reaching the MPP under fast-changing atmospheric conditions, thus influencing the efficiency of PV systems. Intending to improve the performance of PV systems under rapid changes in the atmosphere, this paper proposes model reference adaptive control (MRAC) as a technique for tracking the MPP based on the employ of reference models such as optimal voltage and current at the MPP (VMPP and IMPP). The MATLAB/Simulink environment is used to produce the simulation results; the Kyocera Solar KC 130 GT module is used here as a photovoltaic power plant, connected to a boost converter, supplying a resistive load. The Lyapunov theory was used to demonstrate the stability of the system. The simulation outcomes obtained using the suggested method are compared with those obtained by techniques such as perturb and observe (P&O), incremental conductance (INC), variable step incremental conductance (VSINC), particle swarm optimization (PSO), and grey wolf optimization (GWO), thus showing a very large improvement under standard test and fast-changing atmospheric conditions of the technique proposed on the other techniques in terms of convergence speed and tracking efficiency. The simulation results prove that the suggested method has great tracking effectiveness (>99.88%), less time for convergence (<0.01 s), and simple implementation complexity under fast-changing atmospheric conditions without both transient and steady-state power oscillations, overshoots, and chattering effects, thus causing a great minimization of energy losses, and the proposed technique reaches exactly the MPP under fast-changing atmospheric conditions.http://dx.doi.org/10.1155/2023/5703727 |
| spellingShingle | Yves Abessolo Mindzie Joseph Kenfack Voufo Joseph Urbain Nzotcha Dieudonné Marcel Djanssou Raphael Mbounguen Dynamic Performance Improvement Using Model Reference Adaptive Control of Photovoltaic Systems under Fast-Changing Atmospheric Conditions International Journal of Photoenergy |
| title | Dynamic Performance Improvement Using Model Reference Adaptive Control of Photovoltaic Systems under Fast-Changing Atmospheric Conditions |
| title_full | Dynamic Performance Improvement Using Model Reference Adaptive Control of Photovoltaic Systems under Fast-Changing Atmospheric Conditions |
| title_fullStr | Dynamic Performance Improvement Using Model Reference Adaptive Control of Photovoltaic Systems under Fast-Changing Atmospheric Conditions |
| title_full_unstemmed | Dynamic Performance Improvement Using Model Reference Adaptive Control of Photovoltaic Systems under Fast-Changing Atmospheric Conditions |
| title_short | Dynamic Performance Improvement Using Model Reference Adaptive Control of Photovoltaic Systems under Fast-Changing Atmospheric Conditions |
| title_sort | dynamic performance improvement using model reference adaptive control of photovoltaic systems under fast changing atmospheric conditions |
| url | http://dx.doi.org/10.1155/2023/5703727 |
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