Likelihood Methods for Single-Diode Model Parameter Estimation from Noisy I-V Curve Data

Brian Zaharatos; Mark Campanelli; Clifford Hansen; Keith Emery; Luis Tenorio

doi:10.1109/PVSC.2014.6925526

Likelihood Methods for Single-Diode Model Parameter Estimation from Noisy I-V Curve Data

Brian Zaharatos, Mark Campanelli, Clifford Hansen, Keith Emery, Luis Tenorio

Chemistry and Nanoscience

Research output: Contribution to conference › Paper › peer-review

3 Scopus Citations

Abstract

Characterizing photovoltaic (PV) device performance is important for the growth of the PV industry. Performance is often characterized by a set of key parameters for the PV device in question: open-circuit voltage, short-circuit current, and maximum power. For a wide range of devices, the key performance parameters are a function of the parameters of a single-diode circuit model. In this paper, we present a statistical model for current-voltage-irradiance data of a PV device using a five-parameter single-diode model. The goal is to estimate the single-diode model parameters and key performance parameters with quantified uncertainty. Specifically, we find maximum likelihood estimates, quantify uncertainty via confidence intervals for the model and key performance parameters, and explore two important statistical properties of this model - identifiability and estimability.

Original language	American English
Pages	2850-2855
Number of pages	6
DOIs	https://doi.org/10.1109/PVSC.2014.6925526 https://doi.org/10.1109/PVSC.2014.6925526
State	Published - 15 Oct 2014
Event	40th IEEE Photovoltaic Specialist Conference, PVSC 2014 - Denver, United States Duration: 8 Jun 2014 → 13 Jun 2014

Conference

Conference	40th IEEE Photovoltaic Specialist Conference, PVSC 2014
Country/Territory	United States
City	Denver
Period	8/06/14 → 13/06/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

NREL Publication Number

NREL/CP-5J00-61245

Keywords

likelihood function
maximum likelihood estimator
noise model
parameter estimation
single-diode model

UN SDGs

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

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Cite this

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title = "Likelihood Methods for Single-Diode Model Parameter Estimation from Noisy I-V Curve Data",

abstract = "Characterizing photovoltaic (PV) device performance is important for the growth of the PV industry. Performance is often characterized by a set of key parameters for the PV device in question: open-circuit voltage, short-circuit current, and maximum power. For a wide range of devices, the key performance parameters are a function of the parameters of a single-diode circuit model. In this paper, we present a statistical model for current-voltage-irradiance data of a PV device using a five-parameter single-diode model. The goal is to estimate the single-diode model parameters and key performance parameters with quantified uncertainty. Specifically, we find maximum likelihood estimates, quantify uncertainty via confidence intervals for the model and key performance parameters, and explore two important statistical properties of this model - identifiability and estimability.",

keywords = "likelihood function, maximum likelihood estimator, noise model, parameter estimation, single-diode model",

author = "Brian Zaharatos and Mark Campanelli and Clifford Hansen and Keith Emery and Luis Tenorio",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 40th IEEE Photovoltaic Specialist Conference, PVSC 2014 ; Conference date: 08-06-2014 Through 13-06-2014",

year = "2014",

month = oct,

day = "15",

doi = "10.1109/PVSC.2014.6925526",

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}

Zaharatos, B, Campanelli, M, Hansen, C, Emery, K & Tenorio, L 2014, 'Likelihood Methods for Single-Diode Model Parameter Estimation from Noisy I-V Curve Data', Paper presented at 40th IEEE Photovoltaic Specialist Conference, PVSC 2014, Denver, United States, 8/06/14 - 13/06/14 pp. 2850-2855. https://doi.org/10.1109/PVSC.2014.6925526, https://doi.org/10.1109/PVSC.2014.6925526

TY - CONF

T1 - Likelihood Methods for Single-Diode Model Parameter Estimation from Noisy I-V Curve Data

AU - Zaharatos, Brian

AU - Campanelli, Mark

AU - Hansen, Clifford

AU - Emery, Keith

AU - Tenorio, Luis

PY - 2014/10/15

Y1 - 2014/10/15

N2 - Characterizing photovoltaic (PV) device performance is important for the growth of the PV industry. Performance is often characterized by a set of key parameters for the PV device in question: open-circuit voltage, short-circuit current, and maximum power. For a wide range of devices, the key performance parameters are a function of the parameters of a single-diode circuit model. In this paper, we present a statistical model for current-voltage-irradiance data of a PV device using a five-parameter single-diode model. The goal is to estimate the single-diode model parameters and key performance parameters with quantified uncertainty. Specifically, we find maximum likelihood estimates, quantify uncertainty via confidence intervals for the model and key performance parameters, and explore two important statistical properties of this model - identifiability and estimability.

AB - Characterizing photovoltaic (PV) device performance is important for the growth of the PV industry. Performance is often characterized by a set of key parameters for the PV device in question: open-circuit voltage, short-circuit current, and maximum power. For a wide range of devices, the key performance parameters are a function of the parameters of a single-diode circuit model. In this paper, we present a statistical model for current-voltage-irradiance data of a PV device using a five-parameter single-diode model. The goal is to estimate the single-diode model parameters and key performance parameters with quantified uncertainty. Specifically, we find maximum likelihood estimates, quantify uncertainty via confidence intervals for the model and key performance parameters, and explore two important statistical properties of this model - identifiability and estimability.

KW - likelihood function

KW - maximum likelihood estimator

KW - noise model

KW - parameter estimation

KW - single-diode model

UR - http://www.scopus.com/inward/record.url?scp=84912096605&partnerID=8YFLogxK

U2 - 10.1109/PVSC.2014.6925526

DO - 10.1109/PVSC.2014.6925526

M3 - Paper

AN - SCOPUS:84912096605

SP - 2850

EP - 2855

T2 - 40th IEEE Photovoltaic Specialist Conference, PVSC 2014

Y2 - 8 June 2014 through 13 June 2014

ER -

Likelihood Methods for Single-Diode Model Parameter Estimation from Noisy I-V Curve Data

Abstract

Conference

Bibliographical note

NREL Publication Number

Keywords

UN SDGs

Access to Document

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