Title :
DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm
Author :
Zheng Tan ; Xueguan Song ; Wenping Cao ; Zheng Liu ; Yibin Tong
Author_Institution :
Newcastle Univ., Newcastle upon Tyne, UK
Abstract :
This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine´s previous operational performance, the DFIG´s stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.
Keywords :
IEEE standards; asynchronous generators; finite element analysis; particle swarm optimisation; response surface methodology; rotors; stators; DFIG machine; IEEE standard 112-B; doubly-fed induction generator; finite element method; machine winding; particle swarm optimization; power output maximization; response surface method; rotor windings; stator windings; surrogate optimization algorithm; wind profile data; Optimization; Rotors; Stator windings; Wind speed; Wind turbines; Windings; Doubly fed induction generator; operating conditions; particle swarm optimization; power loss; rewinding; surrogate model; wind power generation;
Journal_Title :
Energy Conversion, IEEE Transactions on
DOI :
10.1109/TEC.2015.2411153
