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2022 Vol.42, Issue 6 Preview Page

Research Article

An Inference Method of Influence Parameters for a Physical Calculation Model of Photovoltaic Power Generation

태양광 발전량의 물리적 계산 모델에 대한 영향 인자 추론 방법

Jiyoon Ku1
,
Myeongchan Oh2
,
Hyun-Goo Kim3
,
Yong-Heack Kang3
,
Hyeong-Dong Park45*
구 지윤1
,
오 명찬2
,
김 현구3
,
강 용혁3
,
박 형동45*
1M.S. Student, Department of Energy Systems Engineering, Seoul National University
2Senior Researcher, New and Renewable Energy Resource Map Laboratory, Korea Institute of Energy Research
3Principal Researcher, New and Renewable Energy Resource Map Laboratory, Korea Institute of Energy Research
4Professor, Department of Energy Resources Engineering, Seoul National University
5Adjunct Researcher, Research Institute of Energy and Resources, Seoul National University
1서울대학교 에너지시스템공학부, 석사과정
2한국에너지기술연구원 신재생자원지도연구실, 선임연구원
3한국에너지기술연구원 신재생자원지도연구실, 책임연구원
4서울대학교 에너지자원공학과, 교수
5서울대학교 에너지자원신기술연구소, 겸임연구원
*Corresponding Author
30 December 2022. pp. 75-91
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Abstract

To cope with the fluctuating and irregular production of solar electricity, a renewable energy generation prediction system, which gives incentives when the forecast error is low, was implemented in Korea in October 2021. Most previous studies have focused on predicting solar irradiance, rather than power output. Physical models are used when the research range is broad, but the accuracy of these models is dependent on the extent of known design parameters. Thus, the purpose of this study was to infer unknown parameters and to examine the effect of applying inferred values on physical model performance. According to sensitivity analysis, azimuth, loss factor, tilt, and albedo had high contributions to the photovoltaic power output, in that order, and together, these parameters accounted for 97% of the output variability. The best prediction accuracy was achieved when azimuth and tilt, which have a high level of interaction, were inferred simultaneously, and an inferred loss factor was also used. As a result, the mean absolute error was 0.079 MWh. The findings of this study may be applied to inferring installation information for solar systems located in abandoned mines and idle sites.

Keywords
Photovoltaic
Solar Power Prediction
Photovoltaic Physical Model
Design Parameters
키워드
태양광
태양광 발전량 예측
태양광 물리 모델
설계 변수
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Information
  • Publisher :Korean Solar Energy Society
  • Publisher(Ko) :한국태양에너지학회
  • Journal Title :Journal of the Korean Solar Energy Society
  • Journal Title(Ko) :한국태양에너지학회 논문집
  • Volume : 42
  • No :6
  • Pages :75-91
  • Received Date : 2022-09-19
  • Revised Date : 2022-11-05
  • Accepted Date : 2022-11-07
  • DOI :https://doi.org/10.7836/kses.2022.42.6.075
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