Bayesian estimation of equivalent circuit parameters of photovoltaic cells

Tada, Kazuya

doi:10.35848/1882-0786/abeb25

Cited by 3 publications

(7 citation statements)

References 29 publications

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“…As an example, the upper limit permitted for I ph surpasses the short-circuit photocurrent magnitude by over tenfold. These are the same as ones used in the previous work [29].…”

Section: Methodsmentioning

confidence: 99%

“…[31]. An initial rough estimation of g(x) was obtained by the piecewise function reported in the original literature, not the softplus-like function developed in the previous work [29]. Although the latter consists of a single analytical equation, it was found that it gives a somewhat worse estimation compared to the former one.…”

Section: Methodsmentioning

confidence: 99%

“…In a previous paper, the author reported on a method for extracting equivalent circuit parameters of solar cells from current-voltage characteristics using Bayesian estimation [29]. The result is not a point estimate of the parameters but an estimated probability distribution of the parameters, and thus, it is also possible to evaluate the error contained in the estimated value.…”

Section: Figurementioning

confidence: 99%

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Accelerating Bayesian Estimation of Solar Cell Equivalent Circuit Parameters Using JAX-Based Sampling

Tada

2023

Electronics

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Equivalent circuit models that reproduce the current–voltage characteristics of solar cells are useful not only to gain physical insight into the power loss mechanisms that take place in solar cells but also for designing systems that use renewable solar energy as a power source. As mentioned in a previous paper, Bayesian estimation of equivalent circuit parameters avoids the drawbacks of nonlinear least-squares methods, such as the possibility of evaluating estimation errors. However, it requires a long computation time because the estimated values are obtained by sampling using a Markov chain Monte Carlo method. In this paper, a trial to accelerate the calculation by upgrading the Bayesian statistical package PyMC is presented. PyMC ver. 4, the next version of PyMC3 used in the previous paper, started to support the latest sampling libraries using a machine learning framework JAX, in addition to PyMC-specific methods. The acceleration effect of JAX is remarkable, achieving a calculation time of less than 1/20 times that of the case without JAX. Recommended calculation conditions were disclosed based on the results of a number of trials, and a demonstration with testable Python code on Google Colaboratory using the recommended conditions is published on GitHub.

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“…As an example, the upper limit permitted for I ph surpasses the short-circuit photocurrent magnitude by over tenfold. These are the same as ones used in the previous work [29].…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

See 1 more Smart Citation

Accelerating Bayesian Estimation of Solar Cell Equivalent Circuit Parameters Using JAX-Based Sampling

Tada

2023

Electronics

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“…This is approximate twice the time required to estimate the one-diode model reported in ref. [14], where the number of samples was an order of magnitude larger.…”

Section: Models and Methodsmentioning

confidence: 99%

“…[11][12][13] Recently, the author reported that the Bayesian estimation is also effective in extracting the equivalent circuit parameters of the one-diode model of a photovoltaic cell. [14] In this article, we used the Bayesian estimation to extract the equivalent circuit parameters in the opposed two-diode model of a photovoltaic cell. In the Bayesian estimation, it is necessary to search the space of the dimension of the number of parameters.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Estimation of Equivalent Circuit Parameters of Photovoltaic Cell with S‐Shaped Current–Voltage Characteristic

Tada

2021

Physica Status Solidi (a)

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An S‐shaped current–voltage characteristic is frequently observed in a photovoltaic cell using emerging materials such as organic semiconductors and organic–inorganic perovskite materials. The opposed two‐diode equivalent circuit model, whose explicit analytical solution is known, can reproduce the S‐shaped characteristic. However, since the number of parameters is as high as eight, it is not easy to extract the equivalent circuit parameters from experimental data by curve fitting. Herein, the Bayesian estimation in extracting the equivalent circuit parameters of the opposed two‐diode model is demonstrated. Unlike the traditional nonlinear least‐squares method, the Bayesian estimation practically does not require any tuning of the initial values and gives the information on the error of the estimates.

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Decreasing Carrier Mobility under Concentrated Illumination and Its Effect on the Series Resistance and Conversion Efficiency of Silicon Concentrator Solar Cells

Harada,

Yamashita,

Ikari

et al. 2024

Physica Status Solidi (a)

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The carrier mobility of solar cell materials is a critical physical parameter that determines the series resistance. Furthermore, series resistance is an essential factor affecting the conversion efficiency of concentrator solar cells under high sunlight illumination. However, there has been slight discussion regarding the relationship between these factors. In the previous study, it was reported that concentrated illumination decreased carrier mobility; however, the scattering mechanism has not yet been clarified. Moreover, carrier–carrier scattering was discussed; however, it did not cause a mobility reduction. Thus effective mass changes are discussed as a possible cause of the decrease in carrier mobility under concentrated illumination. The cause of the decrease in mobility under concentrated sunlight illumination cannot be fully elucidated; however, it is a change in lattice scattering. Furthermore, the effect of the decrease in mobility due to concentrated illumination on the series resistance and conversion efficiency of Si solar cells using numerical calculations is clarified. The increase in the series resistance caused by the mobility reduction is ≈10% under 30 suns.

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Bayesian estimation of equivalent circuit parameters of photovoltaic cells

Cited by 3 publications

References 29 publications

Accelerating Bayesian Estimation of Solar Cell Equivalent Circuit Parameters Using JAX-Based Sampling

Accelerating Bayesian Estimation of Solar Cell Equivalent Circuit Parameters Using JAX-Based Sampling

Bayesian Estimation of Equivalent Circuit Parameters of Photovoltaic Cell with S‐Shaped Current–Voltage Characteristic

Decreasing Carrier Mobility under Concentrated Illumination and Its Effect on the Series Resistance and Conversion Efficiency of Silicon Concentrator Solar Cells

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