Research on State Estimation and Prediction Method of Ship Medium Voltage DC Integrated Power System under Sudden Load Change

The medium voltage DC integrated power system, as the heart of large ships, relies on accurate state acquisition for safe and stable operation. Traditional measurement methods are not sufficient to meet the requirements for accurate data acquisition in complex environments. Extended Kalman filtering is an estimation method that can accurately estimate the current state of the system and predict the state of the system at the next moment. Based on the typical network structure of the medium voltage DC integrated power system on ships, this paper establishes a state space mathematical model of the system, proposes an extended Kalman filtering method for the system under sudden load changes, and achieves state estimation and prediction of the system, enhancing the precision of data acquisition. The effectiveness of the model and algorithm is verified through simulation.