Compensation of CT Distorted Secondary Current Waveform in Online Conditions

Current-transformer (CT) saturation phenomenon impacts the performance of the current-based protective relays and leads them to malfunction; so detecting and resolving such phenomenon are important issues in power system protection. This paper provides a modification for two well-established algorithms: 1) least square error and 2) artificial neural network to compensate and reconstruct CT's distorted secondary current waveform (CTDISCW). The effectiveness of an online algorithm is its operating capability in noisy environments and in the presence of travelling waves generated by any event. In addition, this algorithm must be stable against any normal variation in network structure. Then, both mentioned methods need to be modified to present proper results with an acceptable error in online conditions. In this paper, a real CT is considered to simulate, and a section of the Iranian power network is selected to generate CTDISCWs using the modeled CT, and to evaluate the proposed algorithms' performance.