Research on Non-intrusive Residential Electric Load Identification System Based on SOPC

The high-precision identification of the non-intrusive residential electrical load is an essential technology to realize the intelligentization of the power grid. Due to its low input cost and easy maintenance, this technology has received much attention at home and abroad. In order to improve the accuracy of load identification, this paper proposes a non-intrusive residential electric load monitoring equipment based on system on a programmable chip (SOPC), which is focused on hardware system design, characteristic parameters optimizing and BP neural network algorithm optimization. The feasibility of the system was verified by experimental simulation and tests. The results of experiment show that the method used for hardware design can not only improve the speed of system and most closely match the actual running state of electrical appliances in testing circumstances, but it can also realize the function of load identification rapidly and accurately under the condition of the given residential electricity.