基于GA__BP算法的超导储能装置直接功率控制策略  

Direct power control strategy of superconducting magnetics energy storage device based on GA__BP algorithm

作　　者：张科比 雷勇[1] 

机构地区：[1]四川大学电气信息学院,成都610065

出　　处：《低温与超导》2018年第1期64-68,73,共6页Cryogenics and Superconductivity

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.

关 键 词：遗传算法 神经网络 超导储能 直接功率控制 

分 类 号：TK02[动力工程及工程热物理]