Analysis of solar panel's lumped equivalent circuit parameters using LASSO

Martin Garaj; Henry Shu-Hung Chung; Alan Wai-Lun Lo; Huai Wang

doi:10.1109/ECCE.2019.8912913

Analysis of solar panel's lumped equivalent circuit parameters using LASSO

Martin Garaj
, Henry Shu-Hung Chung
, Alan Wai-Lun Lo
, Huai Wang

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

The power output of a solar panel depends on the level of degradation and external factors, such as temperature and solar irradiation. The changes in the power output caused by temperature and irradiation fluctuations coincide with the changes due to degradation. Therefore, a common way of degradation determination requires the knowledge of external factors. This work investigates a modeling of the panel power output at the reference state without the knowledge of the external factors. Firstly, a sparse regression modeling is used to identify relevant lumped equivalent circuit parameters, which capture the reference state of the solar panel. The p-n junction capacitance is found to be an important indicator of external factors tied to the panel's state of health. Secondly, a set of regression models for modelling the solar panel reference state are tested to distinguish a permanent 5% drop in power output from a regular temperature and irradiation fluctuations, without the information of the temperature and irradiation.

Original language	English
Title of host publication	2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019
Publisher	IEEE
Pages	3427-3432
ISBN (Print)	9781728103952, 9781728103945
DOIs	https://doi.org/10.1109/ECCE.2019.8912913
Publication status	Published - Sept 2019
Event	11th Annual IEEE Energy Conversion Congress and Exposition (ECCE 2019) - Baltimore, United States Duration: 29 Sept 2019 → 3 Oct 2019 https://ieeexplore.ieee.org/xpl/conhome/8897530/proceeding

Publication series

Name	IEEE Energy Conversion Congress and Exposition, ECCE
ISSN (Electronic)	2329-3748

Conference

Conference	11th Annual IEEE Energy Conversion Congress and Exposition (ECCE 2019)
Abbreviated title	IEEE ECCE 2019
Place	United States
City	Baltimore
Period	29/09/19 → 3/10/19
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8897530/proceeding

UN SDGs

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

SDG 7 Affordable and Clean Energy

Research Keywords

Diagnostics
Photovoltaic panel
Regression

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10.1109/ECCE.2019.8912913

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Cite this

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title = "Analysis of solar panel's lumped equivalent circuit parameters using LASSO",

abstract = "The power output of a solar panel depends on the level of degradation and external factors, such as temperature and solar irradiation. The changes in the power output caused by temperature and irradiation fluctuations coincide with the changes due to degradation. Therefore, a common way of degradation determination requires the knowledge of external factors. This work investigates a modeling of the panel power output at the reference state without the knowledge of the external factors. Firstly, a sparse regression modeling is used to identify relevant lumped equivalent circuit parameters, which capture the reference state of the solar panel. The p-n junction capacitance is found to be an important indicator of external factors tied to the panel's state of health. Secondly, a set of regression models for modelling the solar panel reference state are tested to distinguish a permanent 5\% drop in power output from a regular temperature and irradiation fluctuations, without the information of the temperature and irradiation.",

keywords = "Diagnostics, Photovoltaic panel, Regression",

author = "Martin Garaj and Chung, \{Henry Shu-Hung\} and \{Wai-Lun Lo\}, Alan and Huai Wang",

year = "2019",

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booktitle = "2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019",

address = "United States",

note = "11th Annual IEEE Energy Conversion Congress and Exposition (ECCE 2019), IEEE ECCE 2019 ; Conference date: 29-09-2019 Through 03-10-2019",

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Garaj, M, Chung, HS-H, Wai-Lun Lo, A & Wang, H 2019, Analysis of solar panel's lumped equivalent circuit parameters using LASSO. in 2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019., 8912913, IEEE Energy Conversion Congress and Exposition, ECCE, IEEE, pp. 3427-3432, 11th Annual IEEE Energy Conversion Congress and Exposition (ECCE 2019), Baltimore, Maryland, United States, 29/09/19. https://doi.org/10.1109/ECCE.2019.8912913

Analysis of solar panel's lumped equivalent circuit parameters using LASSO. / Garaj, Martin; Chung, Henry Shu-Hung; Wai-Lun Lo, Alan et al.
2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019. IEEE, 2019. p. 3427-3432 8912913 (IEEE Energy Conversion Congress and Exposition, ECCE).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Analysis of solar panel's lumped equivalent circuit parameters using LASSO

AU - Garaj, Martin

AU - Chung, Henry Shu-Hung

AU - Wai-Lun Lo, Alan

AU - Wang, Huai

PY - 2019/9

Y1 - 2019/9

N2 - The power output of a solar panel depends on the level of degradation and external factors, such as temperature and solar irradiation. The changes in the power output caused by temperature and irradiation fluctuations coincide with the changes due to degradation. Therefore, a common way of degradation determination requires the knowledge of external factors. This work investigates a modeling of the panel power output at the reference state without the knowledge of the external factors. Firstly, a sparse regression modeling is used to identify relevant lumped equivalent circuit parameters, which capture the reference state of the solar panel. The p-n junction capacitance is found to be an important indicator of external factors tied to the panel's state of health. Secondly, a set of regression models for modelling the solar panel reference state are tested to distinguish a permanent 5% drop in power output from a regular temperature and irradiation fluctuations, without the information of the temperature and irradiation.

AB - The power output of a solar panel depends on the level of degradation and external factors, such as temperature and solar irradiation. The changes in the power output caused by temperature and irradiation fluctuations coincide with the changes due to degradation. Therefore, a common way of degradation determination requires the knowledge of external factors. This work investigates a modeling of the panel power output at the reference state without the knowledge of the external factors. Firstly, a sparse regression modeling is used to identify relevant lumped equivalent circuit parameters, which capture the reference state of the solar panel. The p-n junction capacitance is found to be an important indicator of external factors tied to the panel's state of health. Secondly, a set of regression models for modelling the solar panel reference state are tested to distinguish a permanent 5% drop in power output from a regular temperature and irradiation fluctuations, without the information of the temperature and irradiation.

KW - Diagnostics

KW - Photovoltaic panel

KW - Regression

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UR - https://www.scopus.com/pages/publications/85076790311#tab=impact

U2 - 10.1109/ECCE.2019.8912913

DO - 10.1109/ECCE.2019.8912913

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781728103952

SN - 9781728103945

T3 - IEEE Energy Conversion Congress and Exposition, ECCE

SP - 3427

EP - 3432

BT - 2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019

PB - IEEE

T2 - 11th Annual IEEE Energy Conversion Congress and Exposition (ECCE 2019)

Y2 - 29 September 2019 through 3 October 2019

ER -

Analysis of solar panel's lumped equivalent circuit parameters using LASSO

Abstract

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