Publicação
MPPT technique based on neural network for photovoltaic system
| Resumo: | The using of an efficient MPPT (Maximum Power Point Tracking) algorithm influences a lot in the global efficiency of the PV system. This thesis presents a detailed study based on simulation of different MPPT algorithms with their features using two systems (off-grid and on-grid). The off-grid system contains a PV array connected to a boost converter and a resistive load. On the off-grid system a simulation is presented using MATLAB/SIMULINK platform with several MPPT algorithms. The simulated MPPT algorithms are the conventionals Incremental Conductance (IncCond), Perturb and Observe (P&O), Open Circuit Voltage (OCV) and a new developed Neural Network (NN) under different environmental conditions of temperature and irradiance. As a result of the simulation, the NN algorithm has a quick response, i.e, it requires less time to reach the MPP and high efficiency and less oscillation comparing with the conventional methods. On the other hand, a single-phase two-stage photovoltaic grid-connected system is simulated which contains a PV array, a boost converter, a dc link capacitor, an inverter, an output L filter and the utility grid. In that system a control of dc link voltage, the injected current and the MPPT is made. Another MPPT algorithm based on NN (modified- NN) was also established. Showed later that is the most suitable for the system. The maximum of power is achieved when the irradiance is maximal and the temperature is minimal. Finally, a study of the influence of the variation in the climatic conditions on the output performance of the system is done. |
|---|---|
| Autores principais: | Abderrahmane, Elhor |
| Assunto: | MPPT Neural network Boost converter PV system |
| Ano: | 2021 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| _version_ | 1867173049136054272 |
|---|---|
| author | Abderrahmane, Elhor |
| author_facet | Abderrahmane, Elhor |
| author_role | author |
| contributor_name_str_mv | Soares, Orlando Abdelfettah, Kerboua Biblioteca Digital do IPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Abderrahmane, Elhor\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Soares, Orlando Abdelfettah, Kerboua Biblioteca Digital do IPB |
| datacite.creators.creator.creatorName.fl_str_mv | Abderrahmane, Elhor |
| datacite.date.Accepted.fl_str_mv | 2021-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2021-12-15T15:17:24Z |
| datacite.date.embargoed.fl_str_mv | 2021-12-15T15:17:24Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | MPPT Neural network Boost converter PV system |
| datacite.titles.title.fl_str_mv | MPPT technique based on neural network for photovoltaic system |
| dc.contributor.none.fl_str_mv | Soares, Orlando Abdelfettah, Kerboua Biblioteca Digital do IPB |
| dc.creator.none.fl_str_mv | Abderrahmane, Elhor |
| dc.date.Accepted.fl_str_mv | 2021-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2021-12-15T15:17:24Z |
| dc.date.embargoed.fl_str_mv | 2021-12-15T15:17:24Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/24500 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | MPPT Neural network Boost converter PV system |
| dc.title.fl_str_mv | MPPT technique based on neural network for photovoltaic system |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | The using of an efficient MPPT (Maximum Power Point Tracking) algorithm influences a lot in the global efficiency of the PV system. This thesis presents a detailed study based on simulation of different MPPT algorithms with their features using two systems (off-grid and on-grid). The off-grid system contains a PV array connected to a boost converter and a resistive load. On the off-grid system a simulation is presented using MATLAB/SIMULINK platform with several MPPT algorithms. The simulated MPPT algorithms are the conventionals Incremental Conductance (IncCond), Perturb and Observe (P&O), Open Circuit Voltage (OCV) and a new developed Neural Network (NN) under different environmental conditions of temperature and irradiance. As a result of the simulation, the NN algorithm has a quick response, i.e, it requires less time to reach the MPP and high efficiency and less oscillation comparing with the conventional methods. On the other hand, a single-phase two-stage photovoltaic grid-connected system is simulated which contains a PV array, a boost converter, a dc link capacitor, an inverter, an output L filter and the utility grid. In that system a control of dc link voltage, the injected current and the MPPT is made. Another MPPT algorithm based on NN (modified- NN) was also established. Showed later that is the most suitable for the system. The maximum of power is achieved when the irradiance is maximal and the temperature is minimal. Finally, a study of the influence of the variation in the climatic conditions on the output performance of the system is done. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| fulltext.url.fl_str_mv | https://bibliotecadigital.ipb.pt/bitstreams/145107a6-9203-4897-92c7-f0acdb06b6bf/download |
| id | ipb_f43bedda3151ba32cbb70c8b4882a987 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10198/24500 |
| instacron_str | ipb |
| institution | Instituto Politécnico de Bragança |
| instname_str | Instituto Politécnico de Bragança |
| language | eng |
| network_acronym_str | ipb |
| network_name_str | Biblioteca Digital do IPB |
| oai_identifier_str | oai:bibliotecadigital.ipb.pt:10198/24500 |
| organization_str_mv | urn:organizationAcronym:ipb |
| person_str_mv | Abderrahmane, Elhor |
| publishDate | 2021 |
| reponame_str | Biblioteca Digital do IPB |
| repository_id_str | urn:repositoryAcronym:ipb |
| service_str_mv | urn:repositoryAcronym:ipb |
| spelling | engpt_PTThe using of an efficient MPPT (Maximum Power Point Tracking) algorithm influences a lot in the global efficiency of the PV system. This thesis presents a detailed study based on simulation of different MPPT algorithms with their features using two systems (off-grid and on-grid). The off-grid system contains a PV array connected to a boost converter and a resistive load. On the off-grid system a simulation is presented using MATLAB/SIMULINK platform with several MPPT algorithms. The simulated MPPT algorithms are the conventionals Incremental Conductance (IncCond), Perturb and Observe (P&O), Open Circuit Voltage (OCV) and a new developed Neural Network (NN) under different environmental conditions of temperature and irradiance. As a result of the simulation, the NN algorithm has a quick response, i.e, it requires less time to reach the MPP and high efficiency and less oscillation comparing with the conventional methods. On the other hand, a single-phase two-stage photovoltaic grid-connected system is simulated which contains a PV array, a boost converter, a dc link capacitor, an inverter, an output L filter and the utility grid. In that system a control of dc link voltage, the injected current and the MPPT is made. Another MPPT algorithm based on NN (modified- NN) was also established. Showed later that is the most suitable for the system. The maximum of power is achieved when the irradiance is maximal and the temperature is minimal. Finally, a study of the influence of the variation in the climatic conditions on the output performance of the system is done.application/pdfpt_PTMPPT technique based on neural network for photovoltaic systemAbderrahmane, ElhorSoares, OrlandoAbdelfettah, KerbouaHostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptURNurn:tid:2028146962021-12-15T15:17:24Z202120202021-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/24500http://purl.org/coar/access_right/c_abf2open accessMPPTNeural networkBoost converterPV system2480605 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesis2021http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/145107a6-9203-4897-92c7-f0acdb06b6bf/download |
| spellingShingle | MPPT technique based on neural network for photovoltaic system Abderrahmane, Elhor MPPT Neural network Boost converter PV system |
| status | SINGLETON |
| subject.fl_str_mv | MPPT Neural network Boost converter PV system |
| title | MPPT technique based on neural network for photovoltaic system |
| title_full | MPPT technique based on neural network for photovoltaic system |
| title_fullStr | MPPT technique based on neural network for photovoltaic system |
| title_full_unstemmed | MPPT technique based on neural network for photovoltaic system |
| title_short | MPPT technique based on neural network for photovoltaic system |
| title_sort | MPPT technique based on neural network for photovoltaic system |
| topic | MPPT Neural network Boost converter PV system |
| topic_facet | MPPT Neural network Boost converter PV system |
| url | http://hdl.handle.net/10198/24500 |
| visible | 1 |