Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Abdelhamid Loukriz"'
Autor:
Bouazza Fekkak, Abdelhamid Loukriz, Ralph Kennel, Hakim Azoug, Abdellah Kouzou, Mohamed Abdelrahem, Mostefa Mohamed-Seghir, Hocine Belmili, Mohamed Menaa
Publikováno v:
2021 IEEE Southern Power Electronics Conference (SPEC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::516c2d08d946f3cef8a57cfcaa711c70
https://doi.org/10.1109/spec52827.2021.9709452
https://doi.org/10.1109/spec52827.2021.9709452
Publikováno v:
International Transactions on Electrical Energy Systems. 31
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dbc4eff6017843354e594db30e1e7635
https://doi.org/10.1002/2050-7038.12882
https://doi.org/10.1002/2050-7038.12882
Publikováno v:
Renewable and Sustainable Energy Reviews. 68:221-233
In this paper, two new Artificial Neural Network MPPT controllers based on fixed and variable step size have been proposed and investigated. The data required to generate the ANN model are generated using the classical Perturbation and Observation al
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7112ef196d56ca9866e9e8a8dfe473f
https://doi.org/10.1016/j.rser.2016.09.131
https://doi.org/10.1016/j.rser.2016.09.131
Publikováno v:
2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe).
Highly efficient and compact multilevel inverters are desirable in many applications such as wind farms, solar energy harvesting and electric vehicles. The authors present a single-phase thirteen level inverter control method employing semiconductor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::11b4b8eee2fedcbfee5fa79affc1d136
https://doi.org/10.1109/eeeic.2017.7977746
https://doi.org/10.1109/eeeic.2017.7977746
Publikováno v:
E3S Web of Conferences, Vol 152, p 01007 (2020)
This paper presents an intelligent method to extract the maximum power from the photovoltaic panel using artificial neural network (ANN). The inputs data required for training the ANN controller are obtained from real weather conditions and the desir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb3f0ca84e1364a16c74f35e953da9fb
https://doi.org/10.1051/e3sconf/202015201007
https://doi.org/10.1051/e3sconf/202015201007
Autor:
Sabir Messalti, Abdelouadoud Loukriz, Sandra Dudley, Abdelhamid Loukriz, Stuart D. Walker, Terence Quinlan
Publikováno v:
2016 8th International Conference on Modelling, Identification and Control (ICMIC).
This paper proposed a Single-Phase 13-level inverter with voltage control method using semiconductor power devices for photovoltaic systems. The multilevel voltage source inverters unique configuration allows them to make high voltages with low harmo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94711f5737b42d6ccb8c5fafc45b60c5
https://doi.org/10.1109/icmic.2016.7804170
https://doi.org/10.1109/icmic.2016.7804170
Publikováno v:
2016 IEEE 17th Workshop on Control and Modeling for Power Electronics (COMPEL).
A voltage-controlled, single-phase, five-level inverter for photovoltaic systems using semiconductor power devices is proposed. Use of a unique, multilevel voltage source configuration allows the production of high voltage, low harmonic distortion AC
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea21880336fda911985482cf4941f078
https://doi.org/10.1109/compel.2016.7556715
https://doi.org/10.1109/compel.2016.7556715
Publikováno v:
ISA transactions. 62
Improvement of the efficiency of photovoltaic system based on new maximum power point tracking (MPPT) algorithms is the most promising solution due to its low cost and its easy implementation without equipment updating. Many MPPT methods with fixed s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b44fa28ba182123227856fc07a02528
https://pubmed.ncbi.nlm.nih.gov/26337741
https://pubmed.ncbi.nlm.nih.gov/26337741