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Development of State Diagnosis Algorithm for Performance Improvement of PV System

태양광전원의 성능향상을 위한 상태진단 알고리즘 개발

  • Choi, Sungsik (Korea University of Technology and Education, Electrical Engineering) ;
  • Kim, Taeyoun (Korea University of Technology and Education, Electrical Engineering) ;
  • Park, Jaebeom (Korea University of Technology and Education, Electrical Engineering) ;
  • Kim, Byungki (Korea University of Technology and Education, Electrical Engineering) ;
  • Rho, Daeseok (Korea University of Technology and Education, Electrical Engineering)
  • 최성식 (한국기술교육대학교 전기전자통신공학부) ;
  • 김태연 (한국기술교육대학교 전기전자통신공학부) ;
  • 박재범 (한국기술교육대학교 전기전자통신공학부) ;
  • 김병기 (한국기술교육대학교 전기전자통신공학부) ;
  • 노대석 (한국기술교육대학교 전기전자통신공학부)
  • Received : 2013.11.19
  • Accepted : 2014.02.05
  • Published : 2014.02.28

Abstract

The installation of PV system to the power distribution system is being increased as one of solutions for environmental pollution and energy crisis. Because the output efficiency of PV system is getting decreased because of the aging phenomenon and several operation obstacles, the technology development of output prediction and state diagnosis of PV modules are required in order to improve operation performance of PV modules. The conventional methods for output prediction by considering various parameters and standard test condition values of PV modules may have difficult and complex computation procedure and also their prediction values may produce large error. To overcome these problems, this paper proposes an optimal prediction algorithm and state diagnosis algorithm of PV modules by using least square methods of linear regression analysis. In addition, this paper presents a state diagnosis evaluation system of PV modules based on the proposed optimal algorithms of PV modules. From the simulation results of proposed evaluation system, it is confirmed that the proposed algorithms is a practical tool for state diagnosis of PV modules.

환경오염과 에너지위기 문제를 해결하기 위하여 세계적으로 태양광전원의 설치가 매년 증가하고 있다. 하지만, 설치된 태양광모듈은 경년열화로 인한 성능저하와 운용상의 다양한 장애요소로 발전량 손실이 발생하여, 태양광모듈의 효율적인 운용을 위한 발전량예측과 상태진단 기술이 요구되고 있다. 기존의 발전량 예측 방법은 많은 파라미터를 고려해야하기 때문에 계산이 복잡하며, 표준시험 조건의 모듈 특성데이터를 사용하기 때문에 오차가 크게 발생한다. 따라서 본 논문에서는 태양광모듈에서 발생하고 있는 문제점을 분석하고 이에 대한 대책을 제시하기 위하여, 선형회귀분석법을 이용한 발전량 예측 알고리즘과 태양광모듈의 상태를 진단하는 알고리즘을 제안하였다. 또한, 이를 바탕으로 태양광모듈의 상태진단 평가시스템을 구현하여 시뮬레이션을 수행한 결과, 기존의 방법에 비하여 제안한 방법이 계산하기 편리하고 예측 오차도 감소함을 확인하였으며, 이상모듈의 상태와 위치를 신속하게 파악할 수 있어, 태양광모듈의 운용효율 향상에 유용함을 확인하였다.

Keywords

References

  1. A. Molki, "Dust affects solar cell efficiency," Physics Education, vol. 45, pp. 456-458, 2010. DOI: http://dx.doi.org/10.1088/0031-9120/45/5/F03
  2. A.R .Gxasheka, "Evaluation of performance parameters of PV modules deployed outdoors," Renewable Energy, vol. 30, pp. 611-620. DOI: http://dx.doi.org/10.1016/j.renene.2004.06.005
  3. E.D. Dunlop, "Lifetime performance of crystalline silicon PV module," 3rd World conference on photovoltaic energy conversion, pp. 2927-2930, 2003.
  4. E.L Meyer and E. Ernest van Dyk, "Assesing the Reliability and Degaadation of Photovoltaic Module Performance Parameters," IEEE TRAN-SACTIONS ON RELIABILITY, 2004. DOI: http://dx.doi.org/10.1109/TR.2004.824831
  5. J.G. Araujo and E. Sanchez, "A new method for experimental determination of the series resistance of a solar cell," Electron Devices, IEEE Transactions on, vol. 29, no. 10, pp. 1511-1513, 1982. DOI: http://dx.doi.org/10.1109/T-ED.1982.20906
  6. K.A. Emery and C.R. Osterwald, "Solar Cell Erriciency Measurements," Solar Cells, vol. 17, pp. 253-374, 1986. DOI: http://dx.doi.org/10.1016/0379-6787(86)90016-5
  7. C. Kao and C.-L. Chyu, "Least-squares estimate in fuzzy regression analysis," European Journal of Operational Research, vol. 148, no. 2, pp. 426-435, 2003. DOI: http://dx.doi.org/10.1016/S0377-2217(02)00423-X
  8. E. Koutroulis and K. Kalaitzakis, "Development of an integrated data acquisition system for renewable energy sources systems monitoring," Renewable Energy, vol. 28, no. 1, pp.139-152, January 2003. DOI: http://dx.doi.org/10.1016/S0960-1481(01)00197-5
  9. N. Forero, J. Hernandez, and G. Gordillo, "Development of a monitoring system for a PV solar plant," Energy Conversion and Management, vol. 47, no. 15-16, pp.2329-2336, September 2006. DOI: http://dx.doi.org/10.1016/j.enconman.2005.11.012
  10. "Result for Aging test of 50kW PV system, KEPCO Research Institute, 2011.
  11. http://www.s-energy.com/fcdata/product/SM-255PC8