Overvoltage Risk Assessment for Renewable Energy Based on Active Control Prediction

With the rapid advancement of new power systems, the integration of renewable energy has raised concerns about overvoltage and system security. Rotor angle swings predominantly influence voltage fluctuations, while the characteristics of active current become less pronounced, complicating overvoltage prediction. This paper proposes a fitting regression prediction method based on statistical analysis, comparing it with two approaches: active current value based on empirical analysis and the LSTM (long short-term memory) algorithm respectively. Each method has distinct advantages and limitations, contributing to voltage prediction and security assessment.