Title :
Design and optimization of control parameters based on direct-drive permanent magnet synchronous generator for wind power system
Author :
Lixia Sun ; Chengya Gong
Author_Institution :
Coll. of Energy & Electr. Eng., Hohai Univ., Nanjing, China
Abstract :
The direct-drive permanent magnet synchronous generator (DDPMSG) for wind power system uses a back-to-back double PWM converter. PI controller based on decoupling control strategies is used to control generator side converter and grid side converter. But the parameters of the PI controller are difficult to obtain correctly. Though manual tuning method is applied to regulate the parameters, the method would waste a lot of time and greatly depend on the experience. The paper analyses the mathematical model of direct-drive permanent magnet synchronous wind power generation system. It presents a particle swarm optimization (PSO) method for determining the parameters of PI controller for PMSG to improve the control ability. PSO is powerful stochastic evolutionary algorithm that is used to find the global optimum solution in search space. Under the condition of wind speed mutation, the simulation results of PMSG system after PI parameter optimization show that the PI control with PSO algorithm can fit the real value. The PSO controller has fast convergence rate, strong adaptability and good dynamic performance.
Keywords :
PI control; PWM power convertors; control system synthesis; electric drives; evolutionary computation; particle swarm optimisation; permanent magnet generators; power generation control; power grids; power system parameter estimation; search problems; stochastic programming; synchronous generators; wind power plants; DDPMSG; PI controller; PSO algorithm; back-to-back double PWM converter; control ability improvement; control parameter design; control parameter optimization; decoupling control strategies; direct-drive permanent magnet synchronous generator; generator side converter control; global optimum solution; grid side converter control; mathematical model; parameter determination; particle swarm optimization; search space; stochastic evolutionary algorithm; wind power generation system; wind power system; wind speed mutation; Generators; Manuals; Mathematical model; Optimization; Permanent magnets; Wind power generation; Wind turbines; Manual Tuning Method; PMSG; Parameter Optimization; Partical Swarm Optimization Algorithm;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2013 8th IEEE Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-6320-4
DOI :
10.1109/ICIEA.2013.6566556