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Voltage Quality Improvement with Neural Network-Based Interline Dynamic Voltage Restorer
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  • Voltage Quality Improvement with Neural Network-Based Interline Dynamic Voltage Restorer
  • Voltage Quality Improvement with Neural Network-Based Interline Dynamic Voltage Restorer
저자명
Aali. Seyedreza,Nazarpour. Daryoush
간행물명
Journal of electrical engineering & technology
권/호정보
2011년|6권 6호|pp.769-775 (7 pages)
발행정보
대한전기학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Custom power devices such as dynamic voltage restorer (DVR) and DSTATCOM are used to improve the power quality in distribution systems. These devices require real power to compensate the deep voltage sag during sufficient time. An interline DVR (IDVR) consists of several DVRs in different feeders. In this paper, a neural network is proposed to control the IDVR performance to achieve optimal mitigation of voltage sags, swell, and unbalance, as well as improvement of dynamic performance. Three multilayer perceptron neural networks are used to identify and regulate the dynamics of the voltage on sensitive load. A backpropagation algorithm trains this type of network. The proposed controller provides optimal mitigation of voltage dynamic. Simulation is carried out by MATLAB/Simulink, demonstrating that the proposed controller has fast response with lower total harmonic distortion.