Smart-Meter based on current transient signal signature and constructive backpropagation method

Increasing of electric power consumption and electricity price are making customers more sensitive in addressing the issues. Therefore, the accuracy of the recording device power consumption (kWh-meter) becomes an absolute necessity to reduce potential conflicts that may arise. This paper proposed prototype of smart-meter which combines transient peak value and steady state values to identify an activity of electrical appliances. These values are used as the identity of electrical appliances that will be taught to Constructive Backpropagation Neural Network (CBP-NN) to record power consumption in detail, including type appliance and time use. The proposed method has very simple structure, it only uses two input (transient peak value and steady state values) and single hidden layer with five neuron. The number of output is equal to the number of appliance. So that, the proposed method implement in microsprocessor system or in standalone product. Simulation and experimental results have validated the performance of the proposed method to operate in a real system