A M-EKF fault detection strategy of insulation system for marine current turbine

Abstract

Abstract Marine current power is a new renewable energy source, it is significant to keep the marine current turbine healthy. But harsh marine conditions, such as regular thermal cycling, high humidity and heavy salt mist, bring severe challenges to the marine current turbine, especially to the winding insulation system. Therefore, it is of great importance to perform fault detection on the insulation system. In this paper, a Modified Extended Kalman Filter (M-EKF) fault detection strategy based on the electrical parametric model derived from the RLC network modeling of Roebel bars is proposed. The proposed fault detection strategy mainly includes two parts. The first step is to establish reasonable state space equations for the model structure extracted to monitor the state of the insulation system. In the second step, the conventional continuous EKF is modified to follow more accurately the state of the marine current turbine. Simulation and experiment results show that the proposed method can realize timely monitoring of the winding insulation system of marine current turbine with good performance.