DEVELOPMENT OF A REGRESSION MATHEMATICAL MODEL FOR DETERMINING THE THERMAL PERFORMANCE OF A PARABOLIC TROUGH SOLAR COLLECTOR

The article presents the development of a regression mathematical model designed to assess the thermal performance of a parabolic trough solar collector (PTC). The main factors included in the model are the density of the solar flux and the temperature of the coolant. The least squares method was used to build the model, which made it possible to minimize deviations between the measured and predicted values of thermal performance. The result of the work is a regression model that enables highly accurate prediction of the thermal power of the PTC in various climatic and operating conditions. The proposed model can be used to improve the accuracy of forecasts and optimize the operation of the PTC, enhancing its energy efficiency in the design and operation of solar PTCs.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-20
DOI
https://doi.org/10.5281/zenodo.17994372
Primary Topic
Solar Thermal and Photovoltaic Systems
Type
article
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article

DEVELOPMENT OF A REGRESSION MATHEMATICAL MODEL FOR DETERMINING THE THERMAL PERFORMANCE OF A PARABOLIC TROUGH SOLAR COLLECTOR

Nurmamat Umaraliyev, Yodgor Аkbarovich Yusupov
Zenodo (CERN European Organization for Nuclear Research)
Solar Thermal and Photovoltaic Systems
article

DEVELOPMENT OF A REGRESSION MATHEMATICAL MODEL FOR DETERMINING THE THERMAL PERFORMANCE OF A PARABOLIC TROUGH SOLAR COLLECTOR

Nurmamat Umaraliyev, Yodgor Аkbarovich Yusupov
article en

Abstract

The article presents the development of a regression mathematical model designed to assess the thermal performance of a parabolic trough solar collector (PTC). The main factors included in the model are the density of the solar flux and the temperature of the coolant. The least squares method was used to build the model, which made it possible to minimize deviations between the measured and predicted values of thermal performance. The result of the work is a regression model that enables highly accurate prediction of the thermal power of the PTC in various climatic and operating conditions. The proposed model can be used to improve the accuracy of forecasts and optimize the operation of the PTC, enhancing its energy efficiency in the design and operation of solar PTCs.

Zenodo (CERN European Organization for Nuclear Research)
Kurgan State University (RU)
Affordable and clean energy
Openalex Percentile: Top 53%
Solar Thermal and Photovoltaic Systems
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