대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 2004년도 하계학술대회 논문집 A
- /
- Pages.202-204
- /
- 2004
신경망을 이용한 전력품질 진단시스템
A Power Quality monitoring system using Neural Network
- 김흥균 (충북대학교 전기전자 컴퓨터공학부) ;
- 이진목 (충북대학교 전기전자 컴퓨터공학부) ;
- 최재호 (충북대학교 전기전자 컴퓨터공학부) ;
-
이상훈
((주)포스콘) ;
- 김재식 ((주)포스콘)
- Kim Hong Kyun (School of electrical and computer, Chungbuk National University) ;
- Lee Jin Mok (School of electrical and computer, Chungbuk National University) ;
- Choi Jea Ho (School of electrical and computer, Chungbuk National University) ;
-
Lee Sang Hoon
(Poscon Ltd) ;
- Kim Jea Sig (Poscon Ltd)
- 발행 : 2004.07.14
초록
This paper presents a neural network technology for the detection and classification of the various types of power quality disturbances. Power quality phenomena are short-time problems and of many varieties. Particularly, the transients happen during very short durations to the nano- and microsecond. Thus, a method for detecting ·md classifying transient signals at the same time and in an automatic combines the properties of the wavelet transform and the advantages of neural networks. We test two neural network and compare the results of Backpropagation Neural (BPN) network with Radial basis function network (RBFN). RBFN is more useful to detect and classify than BPN. The configuration of the hardware of PQ-DAS and some case studies are described.
키워드