Smart Meter based on Time Series Modify and Extreme Learning Machine

The world's economic instability makes people very sensitive to the costs incurred to consume electrical energy. In this paper proposed smart meter that can record the consumption of electrical energy of any electrical equipment. The proposed method is employing Non-Intrusive Load Monitoring (NILM) concept which is combined with time series modify data processing. The advantages of the proposed method are the efficiency of the current signal reader and the least amount of data taken in the training process of artificial neural network Extreme Learning Machine (ELM). The proposed method was using transient signals and steady state signals as sign to identify the condition of equipment ON or OFF. The time series modify method is helpful for data retrieval when many electrical devices are operated. From the experiment results, smart-meter are expected to be utilized to make an electric bill with details of the load usage of any electrical equipment.