Application of electrical nonlinear load harmonic analysis method integrating intelligent sensor data in intelligent agricultural power management

Abstract

In intelligent agricultural power management, the impact of harmonics on the power grid and its operating equipment cannot be ignored. The location of harmonic sources and the amplitude of harmonics injected into the power grid have significant randomness and nonlinearity. In order to accurately locate harmonic sources in the power grid, this paper proposes a method for detecting and locating harmonic sources based on nonlinear loads. This method constructs a judgment network by utilizing the load characteristics of each bus connected to the common connection point (PCC) and the characteristics of each type of load when running separately as training samples, and uses this standard to determine the position of the harmonic source, thereby achieving accurate localization of the harmonic source. In the experiment based on Matlab 2014a simulation platform, the results showed that adding the load characteristic data measured at PCC point in real-time operation to the judgment network can effectively determine the position of the harmonic source. Multiple load tests have shown that the judgment network has high accuracy. The experimental results show that among the 10 samples to be tested, only 2 load samples had misjudgments in their bus positions. In summary, the judgment network based on nonlinear loads can accurately detect and locate the location of harmonic sources in the power grid, and by increasing the number of training data sets, the judgment accuracy can be further improved. Therefore, this method, combined with intelligent sensor data, has high engineering application value for detecting and locating harmonic sources in intelligent agricultural power management.