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Research on Load Identification Based on Load Steady and Transient Signal Processing

机译:基于负载稳态和瞬态信号处理的负载识别研究

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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.
机译:非侵入式负载识别方法是智能电网系统的重要组成部分,而无需进入系统内部。通过这种方式,可以通过测量和分析电力负载来实现电力负荷的识别,包括电压,电流和其他电力信息的入口。为了完善负载识别并提高负载识别率,在稳态和瞬态过程中处理负载信号,并且识别负载。在稳态过程中,负载的功率和电流的谐波特性被合并为粒子群优化算法的适应性函数,并且构造相应的模型以进行稳态过程的相应负载识别。对于瞬态过程,基于交换过程的负载,我们提取导致瞬态过程的负载信号。通过信号处理中的互相关分析,识别提取的负载信号以在瞬态过程下实现负载识别的目的。最后,仿真结果表明,所提出的算法对于负载识别是有效的。

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