The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
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A Study on Vegetative Propagation by Runner Optimization Algorithm-based Maximum Power Point Tracking for Photovoltaic

포복경 영양 번식 최적화 알고리즘 기반 태양전지 최대 전력 점 추적에 관한 연구

  • 정진우 (동신대학교 에너지IoT전공) ;
  • 정경권 (동신대학교, 에너지IoT전공) ;
  • 이태원 (동신대학교, 컴퓨터공학과) ;
  • 박성일 (동신대학교, 정보통신공학과) ;
  • 손영옥 ((주)산정엔지니어링)
  • Received : 2021.04.28
  • Accepted : 2021.06.17
  • Published : 2021.06.30
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Abstract

A Vegetative Propagation by Runner(VPR) Algorithm-based on MPPT Algorithm that can track MPP by adapting to external environmental changes is presented. VPR is an optimization algorithm that mimics the plant ecology of movement and reproduction based on vegetation organs. The VPR algorithm includes a procedure for aging and a procedure for searching the surroundings by rhizomes. Accordingly, it is possible to continuously search around the optimal point. Therefore, the VPR-based MPPT algorithm can continuously search for an optimal point by adapting the changes in the external environment in the process of executing the MPPT algorithm. In this paper, we analyzed the performance of the VPR-based MPPT algorithm by a number of simulations. In addition, the superiority of performance was compared by performance comparison in the same environment as MPPT algorithm based on PSO.

외부 환경변화에 적응하여 MPP를 추적할 수 있는 포복경 영양 번식(VPR; Vegetative Propagation by Runner) 최적화 알고리즘 기반 MPPT 알고리즘을 제시하였다. VPR 알고리즘은 영양기관을 기반으로 군집 이동 번식하는 식물 생태를 모방한 알고리즘으로 식물의 노화 및 부근(Rhizome)에 대한 주변탐색 절차를 수행하여 최적점 인근의 주변을 지속적으로 탐색할 수 있다. 따라서 VPR 기반 MPPT 알고리즘의 경우, MPPT 알고리즘이 수행되는 시점에 발생하는 외부 환경변화에 적응하여 최적점을 탐색할 수 있다. 본 논문에서는 다수의 모의실험을 통해 VPR 기반 MPPT 알고리즘의 성능을 분석하였다. 더불어 PSO(Particle Swarm Optimization) 기반 MPPT 알고리즘과 동일한 환경에서 성능 비교를 통해 성능의 우수성을 비교하였다.

Keywords

Acknowledgement

본 논문은 2020년도 전남테크노파크에서 정책지원단의 2020년 지역수요맟춤형 연구개발사업(연구성과 사업화 지원사업/역량강화 연구개발 지원사업)의 지원으로 수행되었음. (No.202001420001 태양광 발전시스템 스트링단 위의 불균형 현상 개선을 위한 MIC 개발)

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