Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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MPPT Control of Photovoltaic using Neural Network

신경회로망을 이용한 태양광 발전의 MPPT 제어

  • Ko, Jae-Sub (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Choi, Jung-Sik (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Jung, Chul-Ho (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Kim, Do-Yeon (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Jung, Byung-Jin (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Chung, Dong-Hwa (School of Information & Communication Engineering. Sunchon National Univ.)
  • 고재섭 (순천대학교 공과대학 정보통신공학부) ;
  • 최정식 (순천대학교 공과대학 정보통신공학부) ;
  • 정철호 (순천대학교 공과대학 정보통신공학부) ;
  • 김도연 (순천대학교 공과대학 정보통신공학부) ;
  • 정병진 (순천대학교 공과대학 정보통신공학부) ;
  • 정동화 (순천대학교 공과대학 정보통신공학부)
  • Published : 2008.04.25
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Abstract

This paper presents a maximum power point tracking(MPPT) of Photovoltaic system with chopping ratio of DC-DC converter considered load. A variation of solar irradiation is most important factor in the MPPT of PV system. That is nonlinear, aperiodic and complicated. The paper consists of solar radiation source, DC-DC converter, DC motor and load(cf, pump). NN algorithm apply to DC-DC converter through an adaptive control of neural network, calculates converter-chopping ratio using an adaptive control of NN. The results of an adaptive control of NN compared with the results of converter-chopping ratio which are calculated mathematical modeling and evaluate the proposed algorithm. The experimental data show that an adequacy of the algorithm was established through the compared data.

Keywords