Institutional Repository
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/E619DEF3-2055-4BA4-BE9A-DD97E466BA35 | - |
| Identifier | https://doi.org/10.26233/heallink.tuc.83331 | - |
| Language | en | - |
| Extent | 152 pages | en |
| Title | Σχεδίαση ηλεκτρονικού συστήματος ελέγχου για την μεγιστοποίηση της παραγωγής ενέργειας φωτοβολταϊκών συστοιχιών, βασισμένου σε τεχνικές τεχνητής νοημοσύνης | el |
| Title | Design of an electronic control system for maximizing the energy production of photovoltaic arrays, based on artificial intelligence techniques | en |
| Creator | Kalogerakis Christos | en |
| Creator | Καλογερακης Χρηστος | el |
| Contributor [Thesis Supervisor] | Koutroulis Eftychios | en |
| Contributor [Thesis Supervisor] | Κουτρουλης Ευτυχιος | el |
| Contributor [Committee Member] | Lagoudakis Michail | en |
| Contributor [Committee Member] | Λαγουδακης Μιχαηλ | el |
| Contributor [Committee Member] | Kalaitzakis Konstantinos | en |
| Contributor [Committee Member] | Καλαϊτζακης Κωνσταντινος | el |
| Publisher | Πολυτεχνείο Κρήτης | el |
| Publisher | Technical University of Crete | en |
| Academic Unit | Technical University of Crete::School of Electrical and Computer Engineering | en |
| Academic Unit | Πολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών | el |
| Content Summary | The subject of this thesis is the design of an electronic energy management system for maximizing the power generated by a photovoltaic (PV) array. For that purpose, an innovative Maximum Power Point Tracking (MPPT) algorithm was developed, which is based on reinforcement learning, in order to operate the PV array at the Maximum Power Point (MPP) under uniform and non-uniform incident solar irradiation conditions. The PV system under study consists of an MPPT control unit, a DC/DC Boost-type power converter and a battery. For the implementation of the MPPT control system, four different Q-learning-based MPPT methods and a Particle Swarm Optimization-based (PSO) MPPT method were implemented. The Qlearning-based MPPT algorithms were simulated for multiple alternative shading patterns of the PV array and their performance was compared to that of the PSO-based MPPT method. The simulation results demonstrated that the Q-learning-based methods exhibit faster convergence to the global MPP (GMPP) than the PSO-based MPPT method when an appropriate learning process has been applied before their execution. | en |
| Type of Item | Διπλωματική Εργασία | el |
| Type of Item | Diploma Work | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2019-10-01 | - |
| Date of Publication | 2019 | - |
| Subject | MPPT | en |
| Subject | Photovoltaic system | en |
| Subject | Power electronics | en |
| Subject | Q-learning | en |
| Subject | Reinforcement learning | en |
| Bibliographic Citation | Χρήστος Καλογεράκης, "Σχεδίαση ηλεκτρονικού συστήματος ελέγχου για την μεγιστοποίηση της παραγωγής ενέργειας φωτοβολταϊκών συστοιχιών, βασισμένου σε τεχνικές τεχνητής νοημοσύνης ", Διπλωματική Εργασία, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2019 | el |
| Bibliographic Citation | Christos Kalogerakis, "Design of an electronic control system for maximizing the energy production of photovoltaic arrays, based on artificial intelligence techniques", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2019 | en |
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