Abstract
Non-invasive load identification method is an important part of the smart grid system without entering the system inside. By this way can achieve the identification of electricity load by the measurement and analysis of the power load, which includes the entrance of the voltage, current and other power information. In order to perfect the load identification and improve the load recognition rate, the load signal is processed in steady state and transient process, and the load is identified. In the steady state process, the power of the load and the harmonic characteristics of the current are merged as the fitness function of the particle swarm optimization algorithm, and the corresponding model is constructed to carry on the corresponding load identification for the steady state process. For the transient process, based on the load of the switching process, we extract the load signal causing the transient process. Through the cross-correlation analysis in the signal processing, the extracted load signal is identified to achieve the purpose of load identification under transient process. Finally, the simulation results show that the algorithm proposed is effective for the load identification.
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