智能电网态势感知的可视化技术研究与实现

Research and implementation of visualization technology for smart grid situation awareness

为了有效检测电网实时运行状态,识别电网中异常数据信息,现针对智能电网态势感知的可视化技术展开研究与实现。首先利用同步相量测量装置采集电网运行信号,通过小波变换计算不同频率区间的噪声能量阈值,进而实现信号去噪。结合线性判别函数与决策树算法,去除电网中影响态势判断的异常信号,进而实现有效信号的提取,并将其输入LSTM网络中;引入SVDD算法,对电网态势展开可视化识别,根据电网系统内各个运行指标的计算,判断当前电网态势,对潜在风险展开预测,并针对预测结果发出实时预警。实验结果表明,所提方法对电网运行过程中产生的异常数据检测精准度高,对风险的严重性判断准确,能够实现电网态势的确切感知。

In order to effectively detect the real-time operation status of the power grid and identify the abnormal data information in the power grid,the visualization technology of smart grid situation awareness is studied and implemented.Firstly,the synchronous phasor measuring device is used to collect the power grid operation signal,and the noise energy threshold of different frequency ranges is calculated by wavelet transform,so as to realize signal denoising.Combined with linear discriminant function and decision tree algorithm,the abnormal signals affecting the situation judgment in the power grid are removed,and then the effective signals are extracted and input into the LSTM network;The SVDD algorithm is introduced to visually identify the power grid situation,judge the current power grid situation according to the calculation of various operation indicators in the power grid system,predict the potential risks,and issue real-time warning based on the prediction results.The experimental results show that the proposed method has high accuracy in detecting the abnormal data generated during the operation of the power grid,and can accurately judge the severity of the risk,and can realize the accurate perception of the power grid situation.