Development and hardware implementation of a reliable protective relay data acquisition system

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.

► An intelligence based protective relay data acquisition system is proposed. ► A wide range of tests has been performed and encouraging results are obtained. ► Application of this DAS prevents protection system from mal-operation. ► The algorithm is suitable for the real-time application. ► It produces a point by point estimate of the primary signals without any considerable phase error.