Fault Detection and Diagnosis of PV Systems Using Kalman-Filter Algorithm Based on Multi-Zone Polynomial Regression.
| dc.rights.license | open | en_US |
| hal.structure.identifier | ESTIA - Institute of technology [ESTIA] | |
| dc.contributor.author | AL RIFAI, Yehya
ORCID: 0000-0002-7195-2346 | |
| hal.structure.identifier | ESTIA - Institute of technology [ESTIA] | |
| dc.contributor.author | AGUILERA GONZALEZ, Adriana
ORCID: 0000-0003-1166-0648 IDREF: 253127653 | |
| hal.structure.identifier | ESTIA - Institute of technology [ESTIA] | |
| dc.contributor.author | VECHIU, Ionel
ORCID: 0000-0003-4108-3546 IDREF: 102417741 | |
| dc.date.accessioned | 2023-04-04T10:20:44Z | |
| dc.date.available | 2023-04-04T10:20:44Z | |
| dc.date.issued | 2022-11 | |
| dc.date.conference | 2022-11-16 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/172722 | |
| dc.description.abstractEn | Faults must be timely diagnosed, detected, and identified to enhance photovoltaic (PV) system’s dependability. In this context, this paper presents a novel Fault Detection and Diagnosis (FDD) methodology based on a hybrid combination of model-based, through Kalman Filter (KF), and a statistical data-driven regression approach for online monitoring of a PV system’s DC side. This statistical approach is formulated on Multi-Zone non-linear Polynomial regression (MZP) techniques of PV characteristics under Global Maximum Power Points (GMPP) at the array level. In particular, the proposed method effectively detects intermittent soft Short-Circuit (SC) even at very low irradiation. The performance of the proposed FDD methods is evaluated via MATLAB/Simulink® considering varying weather conditions. | |
| dc.language.iso | EN | en_US |
| dc.title.en | Fault Detection and Diagnosis of PV Systems Using Kalman-Filter Algorithm Based on Multi-Zone Polynomial Regression. | |
| dc.type | Communication dans un congrès | en_US |
| dc.subject.hal | Sciences de l'ingénieur [physics]/Energie électrique | en_US |
| bordeaux.hal.laboratories | ESTIA - Recherche | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | Bordeaux INP | en_US |
| bordeaux.institution | Bordeaux Sciences Agro | en_US |
| bordeaux.conference.title | 16th European Workshop on Advanced Control and Diagnosis - ACD2022 | en_US |
| bordeaux.country | fr | en_US |
| bordeaux.conference.city | Nancy | en_US |
| bordeaux.peerReviewed | oui | en_US |
| bordeaux.import.source | hal | |
| hal.identifier | hal-03916297 | |
| hal.version | 1 | |
| hal.export | false | |
| workflow.import.source | hal | |
| dc.rights.cc | Pas de Licence CC | en_US |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2022-11&rft.au=AL%20RIFAI,%20Yehya&AGUILERA%20GONZALEZ,%20Adriana&VECHIU,%20Ionel&rft.genre=unknown |
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