A Digital Twin Approach for Modeling Electrical Characteristics of Bifacial Solar Panels

Jiang Yuan; Zhongbei Tian; Jieming Ma; Ka Lok Man; Baojiang Li

doi:10.1109/IIoTBDSC57192.2022.00065

A Digital Twin Approach for Modeling Electrical Characteristics of Bifacial Solar Panels

Jiang Yuan^*
, Zhongbei Tian
, Jieming Ma
, Ka Lok Man
, Baojiang Li

^*Corresponding author for this work

Electronic, Electrical and Systems Engineering

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

Abstract

Dynamic analysis of a bifacial solar panel's electrical characteristics is essential for controlling and managing the PV system. However, most performance models of bifacial solar panels cannot adapt to changing environments in real-time. This paper proposes a digital twin approach for modelling the electrical characteristics of bifacial solar panels with a dynamic parameter estimation process. The proposed model is based on a double-diode bifacial circuit model. A continuously running four-state Jaya algorithm uses a sliding window dataset of the most recent sensor data to estimate equivalent circuit parameters. With environmental data and optimal parameters, the digital twin model can predict the electrical characteristics of the solar panel. A web-based interface is developed to display relevant digital twin information. Experimental results suggest that the digital twin model can accurately predict the electrical characteristics of an actual bifacial solar panel.

Original language	English
Title of host publication	2022 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC)
Publisher	IEEE
Pages	317-321
Number of pages	5
ISBN (Electronic)	9781665454551
ISBN (Print)	9781665454568 (PoD)
DOIs	https://doi.org/10.1109/IIoTBDSC57192.2022.00065
Publication status	Published - 23 Mar 2023
Event	3rd International Conference on Industrial IoT, Big Data and Supply Chain, IIoTBDSC 2022 - Virtual, Online, China Duration: 23 Sept 2022 → 25 Sept 2022

Publication series

Name	Industrial IoT, Big Data and Supply Chain (IIoTBDSC), International Conference on

Conference

Conference	3rd International Conference on Industrial IoT, Big Data and Supply Chain, IIoTBDSC 2022
Country/Territory	China
City	Virtual, Online
Period	23/09/22 → 25/09/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Bifacial Solar Cell
Digital Twin
Parameter optimization
PV modelling
Solar Energy

ASJC Scopus subject areas

Information Systems and Management
Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Information Systems
Management Science and Operations Research
Civil and Structural Engineering

Access to Document

10.1109/IIoTBDSC57192.2022.00065

Cite this

Yuan, J., Tian, Z., Ma, J., Man, K. L., & Li, B. (2023). A Digital Twin Approach for Modeling Electrical Characteristics of Bifacial Solar Panels. In 2022 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC) (pp. 317-321). Article 10077183 (Industrial IoT, Big Data and Supply Chain (IIoTBDSC), International Conference on). IEEE. https://doi.org/10.1109/IIoTBDSC57192.2022.00065

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title = "A Digital Twin Approach for Modeling Electrical Characteristics of Bifacial Solar Panels",

abstract = "Dynamic analysis of a bifacial solar panel's electrical characteristics is essential for controlling and managing the PV system. However, most performance models of bifacial solar panels cannot adapt to changing environments in real-time. This paper proposes a digital twin approach for modelling the electrical characteristics of bifacial solar panels with a dynamic parameter estimation process. The proposed model is based on a double-diode bifacial circuit model. A continuously running four-state Jaya algorithm uses a sliding window dataset of the most recent sensor data to estimate equivalent circuit parameters. With environmental data and optimal parameters, the digital twin model can predict the electrical characteristics of the solar panel. A web-based interface is developed to display relevant digital twin information. Experimental results suggest that the digital twin model can accurately predict the electrical characteristics of an actual bifacial solar panel.",

keywords = "Bifacial Solar Cell, Digital Twin, Parameter optimization, PV modelling, Solar Energy",

author = "Jiang Yuan and Zhongbei Tian and Jieming Ma and Man, \{Ka Lok\} and Baojiang Li",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 3rd International Conference on Industrial IoT, Big Data and Supply Chain, IIoTBDSC 2022 ; Conference date: 23-09-2022 Through 25-09-2022",

year = "2023",

month = mar,

day = "23",

doi = "10.1109/IIoTBDSC57192.2022.00065",

language = "English",

isbn = "9781665454568 (PoD)",

series = "Industrial IoT, Big Data and Supply Chain (IIoTBDSC), International Conference on",

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Yuan, J, Tian, Z, Ma, J, Man, KL & Li, B 2023, A Digital Twin Approach for Modeling Electrical Characteristics of Bifacial Solar Panels. in 2022 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC)., 10077183, Industrial IoT, Big Data and Supply Chain (IIoTBDSC), International Conference on, IEEE, pp. 317-321, 3rd International Conference on Industrial IoT, Big Data and Supply Chain, IIoTBDSC 2022, Virtual, Online, China, 23/09/22. https://doi.org/10.1109/IIoTBDSC57192.2022.00065

A Digital Twin Approach for Modeling Electrical Characteristics of Bifacial Solar Panels. / Yuan, Jiang; Tian, Zhongbei; Ma, Jieming et al.
2022 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2023. p. 317-321 10077183 (Industrial IoT, Big Data and Supply Chain (IIoTBDSC), International Conference on).

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

TY - GEN

T1 - A Digital Twin Approach for Modeling Electrical Characteristics of Bifacial Solar Panels

AU - Yuan, Jiang

AU - Tian, Zhongbei

AU - Ma, Jieming

AU - Man, Ka Lok

AU - Li, Baojiang

PY - 2023/3/23

Y1 - 2023/3/23

N2 - Dynamic analysis of a bifacial solar panel's electrical characteristics is essential for controlling and managing the PV system. However, most performance models of bifacial solar panels cannot adapt to changing environments in real-time. This paper proposes a digital twin approach for modelling the electrical characteristics of bifacial solar panels with a dynamic parameter estimation process. The proposed model is based on a double-diode bifacial circuit model. A continuously running four-state Jaya algorithm uses a sliding window dataset of the most recent sensor data to estimate equivalent circuit parameters. With environmental data and optimal parameters, the digital twin model can predict the electrical characteristics of the solar panel. A web-based interface is developed to display relevant digital twin information. Experimental results suggest that the digital twin model can accurately predict the electrical characteristics of an actual bifacial solar panel.

AB - Dynamic analysis of a bifacial solar panel's electrical characteristics is essential for controlling and managing the PV system. However, most performance models of bifacial solar panels cannot adapt to changing environments in real-time. This paper proposes a digital twin approach for modelling the electrical characteristics of bifacial solar panels with a dynamic parameter estimation process. The proposed model is based on a double-diode bifacial circuit model. A continuously running four-state Jaya algorithm uses a sliding window dataset of the most recent sensor data to estimate equivalent circuit parameters. With environmental data and optimal parameters, the digital twin model can predict the electrical characteristics of the solar panel. A web-based interface is developed to display relevant digital twin information. Experimental results suggest that the digital twin model can accurately predict the electrical characteristics of an actual bifacial solar panel.

KW - Bifacial Solar Cell

KW - Digital Twin

KW - Parameter optimization

KW - PV modelling

KW - Solar Energy

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U2 - 10.1109/IIoTBDSC57192.2022.00065

DO - 10.1109/IIoTBDSC57192.2022.00065

M3 - Conference contribution

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SN - 9781665454568 (PoD)

T3 - Industrial IoT, Big Data and Supply Chain (IIoTBDSC), International Conference on

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EP - 321

BT - 2022 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC)

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ER -

Yuan J, Tian Z, Ma J, Man KL, Li B. A Digital Twin Approach for Modeling Electrical Characteristics of Bifacial Solar Panels. In 2022 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE. 2023. p. 317-321. 10077183. (Industrial IoT, Big Data and Supply Chain (IIoTBDSC), International Conference on). doi: 10.1109/IIoTBDSC57192.2022.00065

A Digital Twin Approach for Modeling Electrical Characteristics of Bifacial Solar Panels

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this