The smart meter design for total waste of electricity usage costs on household sector calculating using artificial neural network method

This research proposed a Smart Meter design that have a feature to calculate the total wasted energy from electricity usage. This feature obtained by monitoring and scheduling any installed electricity equipment. With this feature, every Smart Meter user expected to be able to manage the use of electronic equipment that installed in each home optimally. In this research artificial neural network with a radial basis network learning algorithm (RBFNN) used to identify any connected device. This method is one of the controlled learning methods and have fast learning speed. To identify the electronic equipment, it used the RMS current rating and the peak value of the wavelet transformation of the RMS current. From the transformation will become input for the RBFNN. Experiment and simulation results show that the Smart Meter with radial basis network method able to identify each load well, where the average training accuracy is 96.76% and the average testing accuracy is 85.08%.