• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
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  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
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Title Coordination Control of ULTC Transformer and STACOM using Kohonen Neural Network
Authors 김광원 ; 이흥재
Page pp.1103-1111
ISSN 1975-8359
Keywords ULTC Transformer ; STACOM ; Coordination Control ; Kohonen Neural Network ; Iterative Condensed Nearest Neighbor Rule
Abstract STACOM will be utilized to control substation voltage in the near future. Although STACOM shows good voltage regulation performance owing to its rapid and continuous response, it needs additional reactive power compensation device to keep control margin for emergency such as fault. ULTC transformer is one of good candidates. This paper presents a Kohonen Neural Network (KNN) based coordination control scheme of ULTC transformer and STACOM. In this paper, the objective function of the coordination control is minimization of both STACOM output and the number of switchings of ULTC transformer while maintaining substation voltage magnitude to the predefined constant value. This coordination, control is performed based on reactive load trend of the substation and KNN which offers optimal tap position in view of STACOM output minimization. The input variables of KNN are active and reactive power of the substation, current tap position, and current STACOM output. The KNN is trained by effective Iterative Condensed Nearest Neighbor (ICNN) rule. This coordination control applied to IEEE 14 bus system and shows satisfactory results.