With the development of big data technology,power system load forecasting has ushered in new opportunities and challenges.The article proposes a power system load forecasting model based on big data technology to address the problems existing in current power system load forecasting.This model integrates heterogeneous data from multiple sources and utilizes machine learning algorithms and deep learning methods to achieve high-precision,real-time,and robust load forecasting.The experimental results show that the model has significant advantages compared to traditional methods,providing strong support for the optimization scheduling and operation control of power systems.
关键词
大数据/电力系统/负荷预测/机器学习/深度学习
Key words
big data/power system/load forecasting/machine learning/deep learning
维普
万方数据