摘要
将遗传算法优化得到的权值赋予神经网络,以消除神经网络的局部最优性。再将这种算法应用到超导储能系统(Superconducting Magnetics Energy Storage,SMES)中,得到一种能够改善超导储能系统响应时间,提高超导储能装置稳定性的直接功率控制策略。仿真结果表明,本文提出的控制策略获得了较好的控制效果,适用于超导储能系统。
The weight obtained by Genetic algorithm optimization was applied to the neural network in order to eliminate the local optimality of the neural network. Then we applied this algorithm to the Superconducting Magnetics Energy Storage to obtain a direct power control strategy which could reduce the response time of Superconducting MagneticsEnergy Storage System and improve the stability of Superconducting Magnetics Energy Storage device. The simulation results show that the control strategy presented in this paper has a better effect on controlling and is suitable for Superconducting Magnetics Energy Storage system.
出处
《低温与超导》
CAS
北大核心
2018年第1期64-68,73,共6页
Cryogenics and Superconductivity
关键词
遗传算法
神经网络
超导储能
直接功率控制
Genetic algorithm, Neural network, Superconducting energy storage, Direct power control
