An adaptive neuro-fuzzy inference system employed cuk converter for PV applications

Neeraj Priyadarshi, Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen, Vigna K. Ramachandaramurthy, Mahajan Sagar Bhaskar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An Adaptive Neuro-Fuzzy Inference System based Intelligent Algorithm for Photovoltaic (PV) application proposed in this paper. Under the nonlinear behavior of the surroundings, the proposed algorithm achieves optimal power point (OPP) without prior system knowledge. Compared with other intelligent methodologies, the proposed algorithm has low implementation cost, as it does not need any sensors to measure solar irradiance. The proposed algorithm provides proper training to the PV system under varying PV insolation. Modeled Cuk converter employed PV system is validate by simulated responses present in the paper. Inverter with Fuzzy logic control (FLC)-dSPACE board is also implement for sinusoidal current injection to the utility grid.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728132020
DOIs
Publication statusPublished - Apr 2019
Event13th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019 - Sonderborg, Denmark
Duration: 23 Apr 201925 Apr 2019

Publication series

NameProceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019

Conference

Conference13th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019
CountryDenmark
CitySonderborg
Period23/04/1925/04/19

Fingerprint

Adaptive Neuro-fuzzy Inference System
Fuzzy inference
DC-DC converters
Converter
Photovoltaic System
Fuzzy Logic Control
D-space
Irradiance
Inverter
Optimal Algorithm
Incident solar radiation
Injection
Fuzzy logic
Grid
Sensor
Methodology
Costs
Sensors

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment

Cite this

Priyadarshi, N., Padmanaban, S., Holm-Nielsen, J. B., Ramachandaramurthy, V. K., & Bhaskar, M. S. (2019). An adaptive neuro-fuzzy inference system employed cuk converter for PV applications. In Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019 [8862398] (Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CPE.2019.8862398
Priyadarshi, Neeraj ; Padmanaban, Sanjeevikumar ; Holm-Nielsen, Jens Bo ; Ramachandaramurthy, Vigna K. ; Bhaskar, Mahajan Sagar. / An adaptive neuro-fuzzy inference system employed cuk converter for PV applications. Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019).
@inproceedings{3c02f37997c54033ac72eeac759e063f,
title = "An adaptive neuro-fuzzy inference system employed cuk converter for PV applications",
abstract = "An Adaptive Neuro-Fuzzy Inference System based Intelligent Algorithm for Photovoltaic (PV) application proposed in this paper. Under the nonlinear behavior of the surroundings, the proposed algorithm achieves optimal power point (OPP) without prior system knowledge. Compared with other intelligent methodologies, the proposed algorithm has low implementation cost, as it does not need any sensors to measure solar irradiance. The proposed algorithm provides proper training to the PV system under varying PV insolation. Modeled Cuk converter employed PV system is validate by simulated responses present in the paper. Inverter with Fuzzy logic control (FLC)-dSPACE board is also implement for sinusoidal current injection to the utility grid.",
author = "Neeraj Priyadarshi and Sanjeevikumar Padmanaban and Holm-Nielsen, {Jens Bo} and Ramachandaramurthy, {Vigna K.} and Bhaskar, {Mahajan Sagar}",
year = "2019",
month = "4",
doi = "10.1109/CPE.2019.8862398",
language = "English",
series = "Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019",
address = "United States",

}

Priyadarshi, N, Padmanaban, S, Holm-Nielsen, JB, Ramachandaramurthy, VK & Bhaskar, MS 2019, An adaptive neuro-fuzzy inference system employed cuk converter for PV applications. in Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019., 8862398, Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019, Institute of Electrical and Electronics Engineers Inc., 13th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019, Sonderborg, Denmark, 23/04/19. https://doi.org/10.1109/CPE.2019.8862398

An adaptive neuro-fuzzy inference system employed cuk converter for PV applications. / Priyadarshi, Neeraj; Padmanaban, Sanjeevikumar; Holm-Nielsen, Jens Bo; Ramachandaramurthy, Vigna K.; Bhaskar, Mahajan Sagar.

Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8862398 (Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - An adaptive neuro-fuzzy inference system employed cuk converter for PV applications

AU - Priyadarshi, Neeraj

AU - Padmanaban, Sanjeevikumar

AU - Holm-Nielsen, Jens Bo

AU - Ramachandaramurthy, Vigna K.

AU - Bhaskar, Mahajan Sagar

PY - 2019/4

Y1 - 2019/4

N2 - An Adaptive Neuro-Fuzzy Inference System based Intelligent Algorithm for Photovoltaic (PV) application proposed in this paper. Under the nonlinear behavior of the surroundings, the proposed algorithm achieves optimal power point (OPP) without prior system knowledge. Compared with other intelligent methodologies, the proposed algorithm has low implementation cost, as it does not need any sensors to measure solar irradiance. The proposed algorithm provides proper training to the PV system under varying PV insolation. Modeled Cuk converter employed PV system is validate by simulated responses present in the paper. Inverter with Fuzzy logic control (FLC)-dSPACE board is also implement for sinusoidal current injection to the utility grid.

AB - An Adaptive Neuro-Fuzzy Inference System based Intelligent Algorithm for Photovoltaic (PV) application proposed in this paper. Under the nonlinear behavior of the surroundings, the proposed algorithm achieves optimal power point (OPP) without prior system knowledge. Compared with other intelligent methodologies, the proposed algorithm has low implementation cost, as it does not need any sensors to measure solar irradiance. The proposed algorithm provides proper training to the PV system under varying PV insolation. Modeled Cuk converter employed PV system is validate by simulated responses present in the paper. Inverter with Fuzzy logic control (FLC)-dSPACE board is also implement for sinusoidal current injection to the utility grid.

UR - http://www.scopus.com/inward/record.url?scp=85074164391&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85074164391&partnerID=8YFLogxK

U2 - 10.1109/CPE.2019.8862398

DO - 10.1109/CPE.2019.8862398

M3 - Conference contribution

AN - SCOPUS:85074164391

T3 - Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019

BT - Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Priyadarshi N, Padmanaban S, Holm-Nielsen JB, Ramachandaramurthy VK, Bhaskar MS. An adaptive neuro-fuzzy inference system employed cuk converter for PV applications. In Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8862398. (Proceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019). https://doi.org/10.1109/CPE.2019.8862398