Theoretical Study on Time Series Data Prediction Method for Coal Fired Power Plants
With the rapid development of smart grids,the coal-fired power plant industry can generate billions of power time se-ries data every day.The analysis and prediction of power time series data have important practical significance for the safe and stable operation of the power system and the rational allocation of resources.In recent years,more and more scholars have be-gun to study the prediction of power time series data.Most existing methods predict future trends by studying the static relation-ships or historical sequence characteristics between multiple power time series data.This article analyzes the research status and related technologies of power time series data prediction methods,which have achieved good application effects in power load forecasting,renewable energy forecasting,fault forecasting,and other fields.
coal-fired power plantstime seriespower time series predictionneural network
万方数据
维普
