摘要
为了提高全钒液流电池(Vanadium redox battery,VRB)储能系统功率控制的快速性,文中提出一种分段量化小脑模型神经网络(piecewise cerebella model articulation controller,PCMAC)与比例积分微分控制(proportion integral differential,PID)相结合的复合控制策略(PCMAC⁃PID),由PCMAC实现前馈控制,PID实现反馈控制。建立了VRB储能系统的数学模型,给出了复合控制器的结构及具体算法,最后通过仿真验证了复合控制策略的有效性。仿真结果表明,与PID算法相比,复合控制策略能更好地提高控制系统的响应速度且具有一定的鲁棒性。
For improving the speedability of power control of Vanadium redox battery(VRB)energy storage system,a compound control strategy(PCMAC⁃PID)in combination of piecewise cerebella model articulation controller(PC⁃MAC)and PID algorithm is proposed in this paper.The feedforward control is realized by the PCMAC and the feed⁃back control is achieved by PID.The mathematical model of VRB energy storage system is set up.The structure and specific algorithm of the compound controller are given.Finally,the effectiveness of the compound control strategy is verified by simulation.The simulation results show that the compound control strategy can,compared to PID algo⁃rithm,improve the response speed of the control system and also has certain robustness.
作者
邱亚
陈薇
李鑫
QIU Ya;CHEN Wei;LI Xin(School of Electrical Engineering and Automation,Hefei University of Technology,Hefei 210009,China)
出处
《高压电器》
CAS
CSCD
北大核心
2023年第7期117-124,共8页
High Voltage Apparatus
基金
安徽省重点研究与开发计划项目(JZ2021AKKG0565)。
关键词
小脑模型神经网络
复合控制
全钒液流电池
功率控制
cerebella model articulation controller
compound control
Vanadium redox battery
power control
