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Development and hardware implementation of a reliable protective relay data acquisition system
Affiliation:1. Siemens Energy Inc., Transmission Division, 110 MacAlyson Court, Cary, NC 27511, United States;2. Illinois Institute of Technology, Department of Electrical and Computer Engineering, 3301S, Dearborn Street, Chicago, IL 60616, United States;1. Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, UK;2. School of Engineering & Materials Science, Queen Mary University London, E1 4NS, UK;1. Croatian Transmission System Operator Ltd., Kupska 4, 10000 Zagreb, Croatia;2. University of Zagreb Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia;1. Wroclaw University of Technology, Wroclaw, Poland;2. Siemens AG, PTD EA, Berlin, Germany;1. Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, College of Nuclear Science and Technology, Harbin Engineering University, 150001 Harbin, Heilongjiang, China;2. School of Electric Power, South China University of Technology, 510641 Guangzhou, Guangdong, China;1. Medical Mycology Research Center, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba, 260-8673, Japan;2. Department of Industrial and Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, P.O. Box 14965-161, Iran;3. Department of Genetics, Faculty of Medical Sciences, Tonekabon Branch, Islamic Azad University, Tonekabon, P.O. Box 48641-61187, Iran;4. Department of Molecular Virology, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba, 260-8670, Japan;1. Electrical Engineering Department, Ecole Nationale Polytechnique Alger, Algiers, Algeria;2. Siemens-Spa Sector-Division Energy Management, 16035 Hydra, Algeria
Abstract:This paper proposes an intelligence based protective relay data acquisition system to correct current transformers and capacitive voltage transformers secondary waveform distortions. The protective relay data acquisition system receives voltage and current signals from current transformers and capacitive voltage transformers and prepares the inputs to the main board after some pre-processing. Current transformers and capacitive voltage transformers provide instrument level current and voltage signals to meters and protective relays in high voltage and extra high voltage systems. The accuracy and performance of protective relays in high voltage and extra high voltage systems are directly related to steady state and transient performance of current transformers and capacitive voltage transformers. Current transformers saturation and capacitive voltage transformers transient could lead to protective relay mal-operation or even prevent tripping. The key of the proposed scheme is to use artificial neural network to achieve the inverse transfer functions of current transformers and capacitive voltage transformers. Simulation studies are preformed and the impacts of changing different parameters are studied. Performance study results show that the proposed scheme is accurate and reliable. The proposed algorithm has also been implemented and tested on a digital signal processor board. Details of the implementation and experimental studies are provided in the paper.
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