Implementation of radial basis function network-based maximum power point tracking for a PV-fed high step-up converter
This research offers a maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems based on neural networks (NNs) and a rapid step-up converter configuration. An improved variable step size-radial basis function network (RBFN) in the NN algorithm is accomplished in the proposed syste...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Energy Research |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2022.915730/full |
| _version_ | 1817999052482019328 |
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| author | Mohan Bharathidasan Vairavasundaram Indragandhi |
| author_facet | Mohan Bharathidasan Vairavasundaram Indragandhi |
| author_sort | Mohan Bharathidasan |
| collection | DOAJ |
| description | This research offers a maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems based on neural networks (NNs) and a rapid step-up converter configuration. An improved variable step size-radial basis function network (RBFN) in the NN algorithm is accomplished in the proposed system to track the maximum power point (MPP) with high convergence speed and obtain maximum power with reduced oscillations. Under various irradiance and temperature conditions, the performance of the recommended algorithm was compared to that of particle swarm optimization (PSO), modified perturb and observe (P&O) MPPT technique, artificial neural network (ANN), and multilayer perceptron feed-forward (MPF) NN-based MPPT method. In this system, a new interleaved non-isolated large step-up converter with the coupled inductor technique is suggested to compensate for the discord in PV devices to enable a continuous and independent power flow. The proposed PV-fed converter system is validated under partial shading conditions (PSCs) and uniform solar PV, and the results are experimentally verified with the use of a programmable direct current (DC) source. The obtained results indicate that the proposed converter produces output with high gain, continuous input current, low voltage stress on switches, minimal ripple, high power density, and extensive input and output operations. Finally, a prototype has been implemented to verify the functionality of the presented converter in continuous conduction mode operation with an input voltage range of 20 V and an output voltage of 200 V. |
| first_indexed | 2024-04-14T03:02:48Z |
| format | Article |
| id | doaj.art-818508eac0e6445ea8d4d53588cdfa94 |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-04-14T03:02:48Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-818508eac0e6445ea8d4d53588cdfa942022-12-22T02:15:51ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2022-08-011010.3389/fenrg.2022.915730915730Implementation of radial basis function network-based maximum power point tracking for a PV-fed high step-up converterMohan BharathidasanVairavasundaram IndragandhiThis research offers a maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems based on neural networks (NNs) and a rapid step-up converter configuration. An improved variable step size-radial basis function network (RBFN) in the NN algorithm is accomplished in the proposed system to track the maximum power point (MPP) with high convergence speed and obtain maximum power with reduced oscillations. Under various irradiance and temperature conditions, the performance of the recommended algorithm was compared to that of particle swarm optimization (PSO), modified perturb and observe (P&O) MPPT technique, artificial neural network (ANN), and multilayer perceptron feed-forward (MPF) NN-based MPPT method. In this system, a new interleaved non-isolated large step-up converter with the coupled inductor technique is suggested to compensate for the discord in PV devices to enable a continuous and independent power flow. The proposed PV-fed converter system is validated under partial shading conditions (PSCs) and uniform solar PV, and the results are experimentally verified with the use of a programmable direct current (DC) source. The obtained results indicate that the proposed converter produces output with high gain, continuous input current, low voltage stress on switches, minimal ripple, high power density, and extensive input and output operations. Finally, a prototype has been implemented to verify the functionality of the presented converter in continuous conduction mode operation with an input voltage range of 20 V and an output voltage of 200 V.https://www.frontiersin.org/articles/10.3389/fenrg.2022.915730/fullcoupled inductorphotovoltaicmaximum power point trackingradial basis function networkhigh step-up converter |
| spellingShingle | Mohan Bharathidasan Vairavasundaram Indragandhi Implementation of radial basis function network-based maximum power point tracking for a PV-fed high step-up converter Frontiers in Energy Research coupled inductor photovoltaic maximum power point tracking radial basis function network high step-up converter |
| title | Implementation of radial basis function network-based maximum power point tracking for a PV-fed high step-up converter |
| title_full | Implementation of radial basis function network-based maximum power point tracking for a PV-fed high step-up converter |
| title_fullStr | Implementation of radial basis function network-based maximum power point tracking for a PV-fed high step-up converter |
| title_full_unstemmed | Implementation of radial basis function network-based maximum power point tracking for a PV-fed high step-up converter |
| title_short | Implementation of radial basis function network-based maximum power point tracking for a PV-fed high step-up converter |
| title_sort | implementation of radial basis function network based maximum power point tracking for a pv fed high step up converter |
| topic | coupled inductor photovoltaic maximum power point tracking radial basis function network high step-up converter |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2022.915730/full |
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