Abstract
The first part of each digital protective relay is data acquisition system (DAS). DAS receives voltage and current signals from current transformers (CTs) and capacitive voltage transformers (CVTs) and prepares the inputs to the main board after some pre-processing. CTs and CVTs provide instrument level current and voltage signals to meters and protective relays in high voltage (HV) and extra high voltage (EHV) systems. The accuracy and performance of protective relays in HV and EHV systems are directly related to steady state and transient performance of CTs and CVTs. CT saturation and CVT transient could lead to protective relay mal-operation or even prevent tripping. This paper proposes an intelligence based DAS to correct CT and CVT secondary waveform distortions. The key of the proposed scheme is to use artificial neural network to achieve the inverse transfer functions of CTs and CVTs. 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.
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