Abstract
This study investigates the multi-objective fuzzy optimization of crowbar resistance for the doubly fed induction generator (DFIG) low-voltage ride-through (LVRT). By integrating the crowbar resistance of the crowbar circuit as a decision variable, a multi-objective model for crowbar resistance value optimization has been established to minimize rotor overcurrent and to simultaneously reduce the DFIG reactive power absorbed from the grid during the process of LVRT. A multi-objective genetic algorithm (MOGA) is applied to solve this optimization problem. In the proposed GA, the value of the crowbar resistance is represented by floating-point numbers in the GA population. The MOGA emphasizes the non-dominated solutions and simultaneously maintains diversity in the non-dominated solutions. A fuzzy-set-theory-based is employed to obtain the best solution. The proposed approach has been evaluated on a 3 MW DFIG LVRT. Simulation results show the effectiveness of the proposed approach for solving the crowbar resistance multi-objective optimization problem in the DFIG LVRT.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
