Title :
Mitigation of Voltage Sag Using Adaptive Neural Network with Dynamic Voltage Restorer
Author :
Banaei, M.R. ; Hosseini, S.H. ; Khajee, M. Darkalee
Author_Institution :
Electr. Eng., Azarbaijan Univ. of Tarbiat Moallem, Tabriz
Abstract :
A dynamic voltage restorer is a power quality (custom power) device used to correct the voltage disturbances by injecting voltage as well as power into the system. The compensation capability of a dynamic voltage restorer (DVR) depends primarily on the maximum voltage injection ability and the amount of stored energy available within the restorer. In this paper a simple structure feed forward neural network is presented for the separate of negative sequence components from fundamental sequence components in unbalance voltage sag. In addition, the strategies of correcting the supply voltage sag in a distribution feeder are presented. In this paper a new control strategy based adaptive neural network is proposed to inject minimum energy for DVR during compensation. Simulation results carried out using PSCAD/EMTDC, verify the effectiveness of the proposed control strategy
Keywords :
feedforward neural nets; power supply quality; power system CAD; power system control; power system restoration; DVR; PSCAD-EMTDC simulation; adaptive neural network; control strategy; dynamic voltage restorer; feed forward neural network; negative sequence component; voltage sag mitigation; Adaptive control; Adaptive systems; Feedforward neural networks; Feeds; Neural networks; PSCAD; Power quality; Power system restoration; Programmable control; Voltage fluctuations; DVR; minimal energy strategy; neural network;
Conference_Titel :
Power Electronics and Motion Control Conference, 2006. IPEMC 2006. CES/IEEE 5th International
Conference_Location :
Shanghai
Print_ISBN :
1-4244-0448-7
DOI :
10.1109/IPEMC.2006.4778093