基于双参考源标定方法的智能变电站合并单元误差自监测技术研究

Research on Error Self-monitoring Technology of Merge Unit in Smart Substations Based on Dual Reference Source Calibration Method

  • 摘要: 针对智能变电站数字计量系统中合并单元误差校准需要全站停电的缺点,提出基于双参考源标定方法的合并单元误差自监测方法。将参考信号注入合并单元传感电路,经A/D采样后通过全相位频谱分析方法提取标准信号特征,根据幅频特性判断合并单元的误差情况。设计主副参考信号保证技术可靠性,解决参考信号在运行过程性能衰减对自监测功能影响的问题。自监测合并单元采用AD9834芯片作为参考信号源的核心部件,利用ARM与FPGA分离并提取信号特征。搭建试验平台测试合并单元的自监测功能,结果表明自监测合并单元电压准确度0.03级,电流准确度0.05级,能够监测传感电路电阻电抗参数变化引起的误差。在模拟实际变电站工程的试验环境中,合并单元可监测±0.05%的电压幅值误差,±2′的电压相位误差,可判断±0.05%的电流幅值误差,±2′的电流相位误差。

     

    Abstract: In order to solve the problem that the merge unit(MU) error calibration needs to outage substation, a self-monitoring method for merge unit errors based on the dual-reference source calibration method is proposed. In this paper, the reference signal is injected into MU acquisition circuit, and after sampling by A/D, the standard signal features are extracted by all-phase spectrum analysis method, and the errors of MU acquisition circuit are judged according to the amplitude-frequency characteristics. The main and secondary reference signals are designed to ensure the technical reliability and solve the problem that the performance attenuation of reference signals during operation affects the self-monitoring function. The AD9834 chip is used as the core component of the reference signal source, the ARM and FPGA are used to separate and extract signal features. A test platform is set up to test the self-monitoring function of the MU. The results show that the voltage accuracy class of the self-monitoring MU is 0.03, the current accuracy class is 0.05. Self-monitoring MU can detect the error caused by the change of the resistance reactance parameter of the acquisition circuit. In the test environment simulating the actual substation project, MU can detect the voltage amplitude error of ±0.05%, the voltage phase error of ±2', and the current amplitude error of ±0.05% and the current phase error of ±2'.

     

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