Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System

Kuan Yu Chou; Chia Shiou Yang; Yon Ping Chen

doi:10.1109/ICCE-Taiwan49838.2020.9258116

Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System

Kuan Yu Chou
, Chia Shiou Yang
, Yon Ping Chen

Institute of Electrical and Control Engineering

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

9 Scopus citations

Abstract

Under the sun insolation in the daytime, the partially shaded effect would easily happen in a photovoltaic (PV) array due to clouds, trees, buildings, etc. To deal with the partially shaded effect, this paper proposes solar global maximum power point tracking (GMPPT) method based on Deep Q-Network. Maximum power point tracking (MPPT) is often used to achieve the maximum power in the PV system. The Perturbation and Observation (PO) method is one of the most popular MPPT techniques in practice. However, due to the use of fixed step size, the PO method may cause undesired oscillation around the maximum power point (MPP). With the partially shaded effect, the characteristic P-V curve of a PV array may possess multi-peaks, which often results in tracking of a local maximum, not the expected global maximum. Demonstrated by experiment results, the proposed Deep Q-Network based solar GMPPT method indeed can track the global MPP faster and more precisely without oscillation.

Original language	English
Title of host publication	2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728173993
DOIs	https://doi.org/10.1109/ICCE-Taiwan49838.2020.9258116
State	Published - 28 Sep 2020
Event	7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 - Taoyuan, Taiwan Duration: 28 Sep 2020 → 30 Sep 2020

Publication series

Name	2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

Conference

Conference	7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
Country/Territory	Taiwan
City	Taoyuan
Period	28/09/20 → 30/09/20

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Global maximum power point tracking (GMPPT)
deep Q-network
partially shaded photovoltaic (PV) system
reinforcement learning

Access to Document

10.1109/ICCE-Taiwan49838.2020.9258116

Cite this

Chou, K. Y., Yang, C. S., & Chen, Y. P. (2020). Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System. In 2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 Article 9258116 (2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-Taiwan49838.2020.9258116

Chou, Kuan Yu ; Yang, Chia Shiou ; Chen, Yon Ping. / Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System. 2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020. Institute of Electrical and Electronics Engineers Inc., 2020. (2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020).

@inproceedings{0eefa01b840b47318a7dab0b3a0ee06e,

title = "Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System",

abstract = "Under the sun insolation in the daytime, the partially shaded effect would easily happen in a photovoltaic (PV) array due to clouds, trees, buildings, etc. To deal with the partially shaded effect, this paper proposes solar global maximum power point tracking (GMPPT) method based on Deep Q-Network. Maximum power point tracking (MPPT) is often used to achieve the maximum power in the PV system. The Perturbation and Observation (PO) method is one of the most popular MPPT techniques in practice. However, due to the use of fixed step size, the PO method may cause undesired oscillation around the maximum power point (MPP). With the partially shaded effect, the characteristic P-V curve of a PV array may possess multi-peaks, which often results in tracking of a local maximum, not the expected global maximum. Demonstrated by experiment results, the proposed Deep Q-Network based solar GMPPT method indeed can track the global MPP faster and more precisely without oscillation.",

keywords = "Global maximum power point tracking (GMPPT), deep Q-network, partially shaded photovoltaic (PV) system, reinforcement learning",

author = "Chou, \{Kuan Yu\} and Yang, \{Chia Shiou\} and Chen, \{Yon Ping\}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 ; Conference date: 28-09-2020 Through 30-09-2020",

year = "2020",

month = sep,

day = "28",

doi = "10.1109/ICCE-Taiwan49838.2020.9258116",

language = "English",

series = "2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020",

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booktitle = "2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020",

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}

Chou, KY, Yang, CS & Chen, YP 2020, Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System. in 2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020., 9258116, 2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020, Institute of Electrical and Electronics Engineers Inc., 7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020, Taoyuan, Taiwan, 28/09/20. https://doi.org/10.1109/ICCE-Taiwan49838.2020.9258116

Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System. / Chou, Kuan Yu; Yang, Chia Shiou; Chen, Yon Ping.
2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9258116 (2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020).

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

TY - GEN

T1 - Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System

AU - Chou, Kuan Yu

AU - Yang, Chia Shiou

AU - Chen, Yon Ping

PY - 2020/9/28

Y1 - 2020/9/28

N2 - Under the sun insolation in the daytime, the partially shaded effect would easily happen in a photovoltaic (PV) array due to clouds, trees, buildings, etc. To deal with the partially shaded effect, this paper proposes solar global maximum power point tracking (GMPPT) method based on Deep Q-Network. Maximum power point tracking (MPPT) is often used to achieve the maximum power in the PV system. The Perturbation and Observation (PO) method is one of the most popular MPPT techniques in practice. However, due to the use of fixed step size, the PO method may cause undesired oscillation around the maximum power point (MPP). With the partially shaded effect, the characteristic P-V curve of a PV array may possess multi-peaks, which often results in tracking of a local maximum, not the expected global maximum. Demonstrated by experiment results, the proposed Deep Q-Network based solar GMPPT method indeed can track the global MPP faster and more precisely without oscillation.

AB - Under the sun insolation in the daytime, the partially shaded effect would easily happen in a photovoltaic (PV) array due to clouds, trees, buildings, etc. To deal with the partially shaded effect, this paper proposes solar global maximum power point tracking (GMPPT) method based on Deep Q-Network. Maximum power point tracking (MPPT) is often used to achieve the maximum power in the PV system. The Perturbation and Observation (PO) method is one of the most popular MPPT techniques in practice. However, due to the use of fixed step size, the PO method may cause undesired oscillation around the maximum power point (MPP). With the partially shaded effect, the characteristic P-V curve of a PV array may possess multi-peaks, which often results in tracking of a local maximum, not the expected global maximum. Demonstrated by experiment results, the proposed Deep Q-Network based solar GMPPT method indeed can track the global MPP faster and more precisely without oscillation.

KW - Global maximum power point tracking (GMPPT)

KW - deep Q-network

KW - partially shaded photovoltaic (PV) system

KW - reinforcement learning

UR - https://www.scopus.com/pages/publications/85098466075

U2 - 10.1109/ICCE-Taiwan49838.2020.9258116

DO - 10.1109/ICCE-Taiwan49838.2020.9258116

M3 - Conference contribution

AN - SCOPUS:85098466075

T3 - 2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

BT - 2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

Y2 - 28 September 2020 through 30 September 2020

ER -

Chou KY, Yang CS, Chen YP. Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System. In 2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9258116. (2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020). doi: 10.1109/ICCE-Taiwan49838.2020.9258116

Deep Q-Network Based Global Maximum Power Point Tracking for Partially Shaded PV System

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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