Artificial Intelligence-Based Fault Tolerant Control Strategy in Wind Turbine Systems

Abstract

Power converters play an important role as an enabling technology in the electric power industry, especially in Wind Energy Systems (WESs). Where they ensure to regulate the exchanging powers between the system and the grid. Therefore; any fault occurs in any parts of these converters for a limited time without eliminating, it may degrade the system stability and performance. This paper presents a new artificial intelligence-based detection method of open switch faults in power converters connecting doubly-fed induction (DFIG) generator wind turbine systems to the grid. The detection method combines a simple Fault Tolerant Control (FTC) strategy with fuzzy logic and uses rotor current average values to detect the faulty switch in a very short period of time. In addition, following a power switch failure, the FTC strategy activates the redundant leg and restores the operation of the converter. In order to improve the performance of the closed-loop system during transients and faulty conditions, current control is based on a PI (proportional-integral) controller optimized using genetic algorithms. The simulation model was developed in Matlab/Simulink environment and the simulation results demonstrate the effectiveness of the proposed FTC method and closed-loop current control scheme