A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle

Adi Kurniawan; Eko Haryanto; A. A. Masroeri

doi:10.1109/ICAMIMIA.2015.7508014

A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle

Adi Kurniawan
, Eko Haryanto
, A. A. Masroeri

Institut Teknologi Sepuluh Nopember

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

11 Citations (Scopus)

Abstract

The application of photovoltaic system on the ship may reduce the operational cost and pollution caused by fossil fuel. In order to optimize the efficiency of the PV system, an appropriate maximum power point tracking (MPPT) must be implemented on the system. The MPPT must have fast response to overcome the rapid changes of solar irradiance due to ship movement or natural occurrence. In this paper, a combination of artificial neural network based MPPT and KY converter is proposed. The proposed method has been validated with a computer based simulation. The results show that the proposed method can optimize the PV system performance with a fast response to the change of sun irradiance.

Original language	English
Title of host publication	ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	117-120
Number of pages	4
ISBN (Electronic)	9781467373463
DOIs	https://doi.org/10.1109/ICAMIMIA.2015.7508014
Publication status	Published - 8 Jul 2016
Event	2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, ICAMIMIA 2015 - Surabaya, Indonesia Duration: 15 Oct 2015 → 16 Oct 2015

Publication series

Name	ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE

Conference

Conference	2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, ICAMIMIA 2015
Country/Territory	Indonesia
City	Surabaya
Period	15/10/15 → 16/10/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

KY converter
artificial neural network (ANN)
maximum power point tracking (MPPT)
photovoltaic (PV)

Access to Document

10.1109/ICAMIMIA.2015.7508014

Cite this

Kurniawan, A., Haryanto, E., & Masroeri, A. A. (2016). A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle. In ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE (pp. 117-120). Article 7508014 (ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAMIMIA.2015.7508014

Kurniawan, Adi ; Haryanto, Eko ; Masroeri, A. A. / A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle. ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 117-120 (ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE).

@inproceedings{166f8b07bfa441d7be220cc4af660edf,

title = "A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle",

abstract = "The application of photovoltaic system on the ship may reduce the operational cost and pollution caused by fossil fuel. In order to optimize the efficiency of the PV system, an appropriate maximum power point tracking (MPPT) must be implemented on the system. The MPPT must have fast response to overcome the rapid changes of solar irradiance due to ship movement or natural occurrence. In this paper, a combination of artificial neural network based MPPT and KY converter is proposed. The proposed method has been validated with a computer based simulation. The results show that the proposed method can optimize the PV system performance with a fast response to the change of sun irradiance.",

keywords = "KY converter, artificial neural network (ANN), maximum power point tracking (MPPT), photovoltaic (PV)",

author = "Adi Kurniawan and Eko Haryanto and Masroeri, \{A. A.\}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, ICAMIMIA 2015 ; Conference date: 15-10-2015 Through 16-10-2015",

year = "2016",

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

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booktitle = "ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE",

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Kurniawan, A, Haryanto, E & Masroeri, AA 2016, A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle. in ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE., 7508014, ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE, Institute of Electrical and Electronics Engineers Inc., pp. 117-120, 2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, ICAMIMIA 2015, Surabaya, Indonesia, 15/10/15. https://doi.org/10.1109/ICAMIMIA.2015.7508014

A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle. / Kurniawan, Adi; Haryanto, Eko; Masroeri, A. A.
ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE. Institute of Electrical and Electronics Engineers Inc., 2016. p. 117-120 7508014 (ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE).

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

TY - GEN

T1 - A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle

AU - Kurniawan, Adi

AU - Haryanto, Eko

AU - Masroeri, A. A.

PY - 2016/7/8

Y1 - 2016/7/8

N2 - The application of photovoltaic system on the ship may reduce the operational cost and pollution caused by fossil fuel. In order to optimize the efficiency of the PV system, an appropriate maximum power point tracking (MPPT) must be implemented on the system. The MPPT must have fast response to overcome the rapid changes of solar irradiance due to ship movement or natural occurrence. In this paper, a combination of artificial neural network based MPPT and KY converter is proposed. The proposed method has been validated with a computer based simulation. The results show that the proposed method can optimize the PV system performance with a fast response to the change of sun irradiance.

AB - The application of photovoltaic system on the ship may reduce the operational cost and pollution caused by fossil fuel. In order to optimize the efficiency of the PV system, an appropriate maximum power point tracking (MPPT) must be implemented on the system. The MPPT must have fast response to overcome the rapid changes of solar irradiance due to ship movement or natural occurrence. In this paper, a combination of artificial neural network based MPPT and KY converter is proposed. The proposed method has been validated with a computer based simulation. The results show that the proposed method can optimize the PV system performance with a fast response to the change of sun irradiance.

KW - KY converter

KW - artificial neural network (ANN)

KW - maximum power point tracking (MPPT)

KW - photovoltaic (PV)

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U2 - 10.1109/ICAMIMIA.2015.7508014

DO - 10.1109/ICAMIMIA.2015.7508014

M3 - Conference contribution

AN - SCOPUS:84981287180

T3 - ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE

SP - 117

EP - 120

BT - ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, ICAMIMIA 2015

Y2 - 15 October 2015 through 16 October 2015

ER -

Kurniawan A, Haryanto E, Masroeri AA. A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle. In ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE. Institute of Electrical and Electronics Engineers Inc. 2016. p. 117-120. 7508014. (ICAMIMIA 2015 - International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation, Proceeding - In conjunction with Industrial Mechatronics and Automation Exhibition, IMAE). doi: 10.1109/ICAMIMIA.2015.7508014

A neural network based maximum power point tracker with KY converter for photovoltaic system on a moving vehicle

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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