Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm

Luis D. Murillo-Soto; Geovanni Figueroa-Mata; Carlos Meza

doi:10.1109/IWOBI.2018.8464197

Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

One of the main concern of the maintenance operation in solar plants is the early identification of faults in solar panels. Several faults in solar panels reflects on the variation of its internal resistance. This work presents and validates a differential evolution algorithm that is capable of identifying the changes on the internal resistance of photo-voltaic (PV) modules under dark conditions. Such algorithm enables the automated test of PV modules during the night, when the identification operations do not affect the PV installation energy generation.

Original language	English
Title of host publication	2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781538675069
DOIs	https://doi.org/10.1109/IWOBI.2018.8464197
State	Published - 12 Sep 2018
Event	2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - San Carlos, Costa Rica Duration: 18 Jul 2018 → 20 Jul 2018

Publication series

Name	2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings

Conference

Conference	2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018
Country/Territory	Costa Rica
City	San Carlos
Period	18/07/18 → 20/07/18

Keywords

Dark conditions model
Differential evolution algorithm
Explicit dark condition model
Photo-voltaic module

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10.1109/IWOBI.2018.8464197

Cite this

Murillo-Soto, L. D., Figueroa-Mata, G., & Meza, C. (2018). Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm. In 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings Article 8464197 (2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWOBI.2018.8464197

Murillo-Soto, Luis D. ; Figueroa-Mata, Geovanni ; Meza, Carlos. / Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm. 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. (2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings).

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title = "Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm",

abstract = "One of the main concern of the maintenance operation in solar plants is the early identification of faults in solar panels. Several faults in solar panels reflects on the variation of its internal resistance. This work presents and validates a differential evolution algorithm that is capable of identifying the changes on the internal resistance of photo-voltaic (PV) modules under dark conditions. Such algorithm enables the automated test of PV modules during the night, when the identification operations do not affect the PV installation energy generation.",

keywords = "Dark conditions model, Differential evolution algorithm, Explicit dark condition model, Photo-voltaic module",

author = "Murillo-Soto, \{Luis D.\} and Geovanni Figueroa-Mata and Carlos Meza",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 ; Conference date: 18-07-2018 Through 20-07-2018",

year = "2018",

month = sep,

day = "12",

doi = "10.1109/IWOBI.2018.8464197",

language = "Ingl{\'e}s",

isbn = "9781538675069",

series = "2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings",

}

Murillo-Soto, LD , Figueroa-Mata, G & Meza, C 2018, Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm. in 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings., 8464197, 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018, San Carlos, Costa Rica, 18/07/18. https://doi.org/10.1109/IWOBI.2018.8464197

Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm. / Murillo-Soto, Luis D.; Figueroa-Mata, Geovanni ; Meza, Carlos.
2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8464197 (2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm

AU - Murillo-Soto, Luis D.

AU - Figueroa-Mata, Geovanni

AU - Meza, Carlos

PY - 2018/9/12

Y1 - 2018/9/12

N2 - One of the main concern of the maintenance operation in solar plants is the early identification of faults in solar panels. Several faults in solar panels reflects on the variation of its internal resistance. This work presents and validates a differential evolution algorithm that is capable of identifying the changes on the internal resistance of photo-voltaic (PV) modules under dark conditions. Such algorithm enables the automated test of PV modules during the night, when the identification operations do not affect the PV installation energy generation.

AB - One of the main concern of the maintenance operation in solar plants is the early identification of faults in solar panels. Several faults in solar panels reflects on the variation of its internal resistance. This work presents and validates a differential evolution algorithm that is capable of identifying the changes on the internal resistance of photo-voltaic (PV) modules under dark conditions. Such algorithm enables the automated test of PV modules during the night, when the identification operations do not affect the PV installation energy generation.

KW - Dark conditions model

KW - Differential evolution algorithm

KW - Explicit dark condition model

KW - Photo-voltaic module

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U2 - 10.1109/IWOBI.2018.8464197

DO - 10.1109/IWOBI.2018.8464197

M3 - Contribución a la conferencia

AN - SCOPUS:85054522873

SN - 9781538675069

T3 - 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings

BT - 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018

Y2 - 18 July 2018 through 20 July 2018

ER -

Murillo-Soto LD , Figueroa-Mata G , Meza C. Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm. In 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. 8464197. (2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings). doi: 10.1109/IWOBI.2018.8464197

Identification of the Internal Resistance in Solar Modules under Dark Conditions Using Differential Evolution Algorithm

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