LAUSR

Measurement current transformers (MCTs) are an important component in the measurement of electric power. In this era of deregulation, every power distribution company strives for maximum revenue. It could be possible if the errors present in MCTs are reduced. Maharashtra State Electricity Distribution Company (MSEDCL) is one of the power distribution utility in India interested to resolve its problems regarding MCT error compensation. In this article, the MCT error compensation problem was tackled for various operating conditions. These conditions include metrological properties of core, transformation ratio, burden, remanent flux and nature and quantum of load connected on the primary side of MCT. The MCT secondary side waveform is analyzed for various operating conditions, and from these data, the artificial neural network (ANN) is trained. Implementation of the compensation system and data acquisition is done using dSPACE 1104 software. Experimentation is performed in MSEDCL laboratory, and test results demonstrate the effectiveness of the proposed system.