Panel‐based stratified cluster sampling and analysis for photovoltaic outdoor measurements

Pepelyshev, Andrey; Sovetkin, Evgenii; Steland, Ansgar

doi:10.1002/asmb.2217

Cited by 4 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The machine learning counterpart may become an effective alternative to the present SDE if a weather forecasting problem having a higher degree of freedom is encountered. Degradation of PV systems is a problem faced in the real world as well. The performance index to be optimized should be extended if additional dynamics to be controlled, such as vegetation in greenhouses, are considered.…”

Section: Discussionmentioning

confidence: 99%

An optimal switching approach toward cost‐effective control of a stand‐alone photovoltaic panel system under stochastic environment

Yoshioka

Yano

2019

Appl Stoch Models Bus & Ind

View full text Add to dashboard Cite

The operation of a stand‐alone photovoltaic (PV) system ultimately aims for the optimization of its energy storage. We present a mathematical model for cost‐effective control of a stand‐alone system based on a PV panel equipped with an angle adjustment device. The model is based on viscosity solutions to partial differential equations, which serve as a new and mathematically rigorous tool for modeling, analyzing, and controlling PV systems. We formulate a stochastic optimal switching problem of the panel angle, which is here a binary variable to be dynamically controlled under stochastic weather condition. The stochasticity comes from cloud cover dynamics, which is modeled with a nonlinear stochastic differential equation. In finding the optimal control policy of the panel angle, switching the angle is subject to impulsive cost and reduces to solving a system of Hamilton‐Jacobi‐Bellman quasi‐variational inequalities (HJBQVIs). We show that the stochastic differential equation is well posed and that the HJBQVIs admit a unique viscosity solution. In addition, a finite‐difference scheme is proposed for the numerical discretization of HJBQVIs. A demonstrative computational example of the HJBQVIs, with emphasis on a stand‐alone experimental system, is finally presented with practical implications for its cost‐effective operation.

show abstract

Section: Discussionmentioning

confidence: 99%

An optimal switching approach toward cost‐effective control of a stand‐alone photovoltaic panel system under stochastic environment

Yoshioka

Yano

2019

Appl Stoch Models Bus & Ind

View full text Add to dashboard Cite

show abstract

“…A LSSM is a system of linear equations, where the observation equations are amended by state equations, whereby the latent state variables are solely responsible for autoregressive dynamics. Some prominent examples of various LSSM applications to economic and financial time series are given, for example, in References 4‐10. A recent comprehensive review of developments in LSSMs is provided by Durbin and Koopman (2012) 11 …”

Section: Introductionmentioning

confidence: 99%

Testing for parameter changes in linear state space models

Golosnoy

Köhler

Schmid

et al. 2021

Appl Stoch Models Bus & Ind

View full text Add to dashboard Cite

Linear state space models (LSSMs) provide a very general framework for multiple time series analysis. We propose a novel statistical procedure for testing validity of a LSSM which is focused on the detection of changes in parameters of the given LSSM. We derive the moments as well as the asymptotic distribution of the test statistic, and investigate the test size and the test power for changes in means, variances, and autoregressive coefficients. In the empirical application we test the validity of LSSMs applied to daily realized volatility time series.

show abstract

“…The approach presented in this paper has been used to preprocess a large number of EL images collected in a panel-type multi-site study [1], in order to prepare them for further statistical analyses. Tailored multiple regression methods have been proposed by [2] and applied to images preprocessed using the method proposed here. In practice, one often computes certain quality features from the sampled images, and it is even possible to calculate the operating voltage of individual solar cells by EL imaging, [3].…”

Section: Introductionmentioning

confidence: 99%

Automatic processing and solar cell detection in photovoltaic electroluminescence images

Sovetkin¹,

Steland²

2019

ICA

Self Cite

View full text Add to dashboard Cite

Electroluminescence (EL) imaging is a powerful and established technique for assessing the quality of photovoltaic (PV) modules, which consist of many electrically connected solar cells arranged in a grid. The analysis of imperfect real-world images requires reliable methods for preprocessing, detection and extraction of the cells. We propose several methods for those tasks, which, however, can be modified to related imaging problems where similar geometric objects need to be detected accurately. Allowing for images taken under difficult outdoor conditions, we present methods to correct for rotation and perspective distortions. The next important step is the extraction of the solar cells of a PV module, for instance to pass them to a procedure to detect and analyze defects on their surface. We propose a method based on specialized Hough transforms, which allows to extract the cells even when the module is surrounded by disturbing background and a fast method based on cumulated sums (CUSUM) change detection to extract the cell area of single-cell mini-module, where the correction of perspective distortion is implicitly done. The methods are highly automatized to allow for big data analyses. Their application to a large database of EL images substantiates that the methods work reliably on a large scale for real-world images. Simulations show that the approach achieves high accuracy, reliability and robustness. This even holds for low contrast images as evaluated by comparing the simulated accuracy for a low and a high contrast image.

show abstract

Panel‐based stratified cluster sampling and analysis for photovoltaic outdoor measurements

Cited by 4 publications

References 10 publications

An optimal switching approach toward cost‐effective control of a stand‐alone photovoltaic panel system under stochastic environment

An optimal switching approach toward cost‐effective control of a stand‐alone photovoltaic panel system under stochastic environment

Testing for parameter changes in linear state space models

Automatic processing and solar cell detection in photovoltaic electroluminescence images

Contact Info

Product

Resources

About