基于量子滤波器的电能数据检测与分析

随着以智能电表为核心的智能电网快速发展,电力大数据吸引了用户、用电企业、政府的注意力.用电数据容易受到各种未知的随机干扰.探索了将自适应滤波技术引入电网信息监测.而由于用电负荷曲线复杂、不能给出一个具体的模型,利用量子递归神经网络构造了一个与模型无关的智能滤波器.最后提出了利用量子滤波器进行电力负荷预测以及利用测量误差的概率密度函数进行用户异常用电检测的设想.

Detection and analysis of energy data by using quantum filter

With the rapid development of smart power grid as the core of smart meters,power big data has attracted the attention of users,power companies and the government.The introduction of adaptive filtering into the power grid information monitoring was explored.Due to the complexity of the power load curve,specific model cannot be described.A model-independent intelligent filter was constructed by using the recurrent quantum neural network.The quantum filter was tried to use in the power load forecasting and abnormal electrical testing.