Estimation of Power Using PV System Model Formula and Machine Learning

Hyun Gyu Oh; Woo Gyun Shin; Young Chul Ju; Soo Hyun Bae; Hye Mi Hwang; Gi Hwan Kang; Suk Whan Ko; Hyo Sik Chang

doi:10.21218/CPR.2023.11.1.027

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2023 Vol.11, Issue 1 Preview Page Next Page

Estimation of Power Using PV System Model Formula and Machine Learning 태양광시스템 모델식과 기계학습을 이용한 발전성능 추정

31 March 2023. pp. 27-33

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Abstract

In this paper, a machine learning model by using a regression algorithm is proposed to estimate the power generation performance of the BIPV system. The physical model formula for estimating the generation performance and the proposed model were compared and analyzed. For the physical model formula, simple efficiency model, temperature correction model, and regressive physics model for changing an irradiance were used. As a result, when comparing the regressive physics model for changing an irradiance and the proposed model with the actual generation measured data, the respective RMSE values are 0.1497 kW, 0.0451 kW and the accuracy values are 86.44%, and 96.56%. Therefore, the proposed model implemented in this experiment can be useful in estimating power generation.

Keywords

BIPV

Machine learning

Linear model

Root mean square error

References

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Information

Publisher :Korea Photovoltaic Society
Publisher(Ko) :한국태양광발전학회
Journal Title :Current Photovoltaic Research
Volume : 11
No :1
Pages :27-33
Received Date : 2023-02-15
Revised Date : 2023-02-28
Accepted Date : 2023-03-06
DOI :https://doi.org/10.21218/CPR.2023.11.1.027

Current Photovoltaic Research ISSN:2288-3274(Print) 2508-125X(Online)

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