Research on Load Forecasting and Anomaly Detection Methods for Power Grids Based on Deep Neural Networks
In practical work,the accuracy of power grid load forecasting and anomaly detection model is not enough,which leads to different degrees of deviation in the prediction and detection results,especially in the time content of power grid load forecasting and anomaly detection.Therefore,the research on power grid load forecasting and anomaly detection based on deep neural network has effective theoretical significance and practical value for improving power grid load forecasting and anomaly detection methods.By expounding the relevant theories,this paper provides a theoretical basis for the research,and introduces two methods of power grid load forecasting and anomaly detection based on deep neural network,so as to further promote the development and construction of power grid operation safety and stability.
deep neural networkpower grid load forecastinganomaly detection
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