Development of an electronic device with wireless interface for measuring and monitoring residential electrical loads using the non-invasive method

The increase in the demand for electricity in the last decades has forced consumers to adopt strong rationing measures. However, these actions, often evidenced in small intuitive ways of reducing consumption, are not enough to improve energy efficiency. The user’s awareness needs to be accompanied by increasingly interactive and autonomous tools that allow them to know the true dimension of the financial impact on the inadequate use of domestic electrical and electronic equipment. In this sense, a wireless electronic device capable of noninvasively acquiring signals from household mains installed in a residence was developed so that the system can identify the connected equipment in the electrical network and how much it is contributing to power consumption. After the measurement by the developed device, your performance was compared with two energy analyzers in the market where the loads were disaggregated and classified with the Pearson’s correlation and using an ANN (artificial neural network). Analysis of the test results revealed that the ANN was more efficient in classifying loads, in comparison with the Pearson’s method, with 91% accuracy of the device proposed in this work.