Research on Power Supply Capacity Load Warning Based on Machine Learning

The stability and security of power supply have become increasingly prominent issues. To address this issue, this paper proposes a machine learning-based power supply capacity load early warning technology. This technology can accurately predict the power grid load in real time through machine learning combined with LSTM network using power information from different sources, evaluate whether the feeder is overloaded based on the load prediction results, and set up early warning rules to warn the power grid about its load operation status, improving the stability and security of the power system.