Journal of the Korean Institute of Illuminating and Electrical Installation Engineers (조명전기설비학회논문지)

The Korean Institute of IIIuminating and Electrical Installation Engineers (한국조명전기설비학회)
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Development of Neural Network Controller for Maximum Power Point Tracking of PV System

PV 시스템의 최대전력점 추적을 위한 신경회로망 제어기 개발

  • Published : 2009.01.31
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Abstract

This paper presents an Neural Network(NN) controller for Maximum Power Point Tracking (MPPT) of PV supplied DC motor. A variation of solar irradiation is most important factor in the MPPT of PV system. That is nonlinear, aperiodic and complicated. NN was widely used due to easily solving a complex math problem. Proposed photovoltaic system consists of NN, 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.

본 논문은 DC 전동기에 공급되는 PV 시스템의 최대전력점추적에 대한 신경회로망 제어기를 제시한다. 다양한 일사량은 PV 시스템의 MPPT에 대하여 가장 중요한 요소이다. 일사량은 비선형적, 비주기적이고 복잡하다. 신경회로망은 복잡한 수학적 문제를 해결하는데 광범위하게 사용되고 있다. 제안한 태양광 발전시스템은 신경회로망 제어기, DC-DC 컨버터, DC전동기, 부하로 구성되어 있다. 신경회로망 알고리즘은 컨버터의 쵸핑비를 계산하고 DC-DC 컨버터에 적용된다. 신경회로망의 출력은 수학적 모델링에 의해 계산된 값과 비교하고 알고리즘의 타당성을 제시한다.

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References

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