Research on Power System Load Forecasting Based on Deep Learning Algorithms
This uses deep learning algorithm to carry out in-depth research on power system load forecasting.Firstly,the historical data of the power system is fully analyzed,and the load data set with temporal and spatial correlation is established.Secondly,deep learning models such as Convolutional Neural Networks and Long Short-Term Memory are used to achieve efficient feature extraction and temporal modeling of load data.Finally,after model training and validation,the robustness and accuracy of the proposed algorithm are verified under different seasons and load fluctuations.
deep learning algorithmspower systemload forecastingconvolutional neural networklong short-term memory
NETL
NSTL
万方数据
