摘要
优化电解碲电源对电解行业节能增效、提高电解产品质量和改善电网环境具有重要意义.电源前级采用三相电压型PWM整流器;在建立PWM整流器数学模型的基础上,通过改进双闭环PI控制策略,即外环基于并行搜索全局寻优的遗传算法优化BP神经网络权值和阈值的智能控制方法,分析网侧电流波形和谐波含量,可得到所需的额定电解电压和电流;以MATLAB/Simulink软件为平台进行仿真计算.结果表明:GA-BP(Genetic algorithm-Back propagation)算法具有输出电压平稳、响应速度快、超调量小、抗干扰性强等优点.
Optimizing tellurium electrolyte power is of great significance to save energy,improve efficiency,improve the quality of electrolytic products and grid environment in electrolytic industry.The three-phase voltage source PWM rectifier is used in the front stage of power supply,and an optimized mathematical model is established.By improving the double closed-loop PI control strategy,in which parallel global-optimal genetic algorithm is used to optimize the weights and thresholds of BP neural network in the outer loop,the current waveform and harmonic content in grid side are analyzed,and rated electrolytic voltage and current can be further obtained.Finally,based on MATLAB simulation,this work shows that GA-BP algorithm has the advantages of stable output voltage,fast response,small overshoot and strong anti-interference.
作者
刘静
柳成
曲永印
LIU Jing;LIU Cheng;QU Yongyin(School of Electrical and Information Engineering,Beihua University,Jilin 132021,China;Jilin Institute of Chemical Technology,Jilin 130022,China)
出处
《北华大学学报（自然科学版）》
CAS
2020年第2期257-262,共6页
Journal of Beihua University（Natural Science）
基金
吉林省发展和改革委员会项目(2018C035-1)
吉林省科技厅中青年科技创新领军人才及团队项目(20190101018JH)
北华大学研究生创新计划项目(2019048).
关键词
电解碲
遗传算法
BP神经网络
MATLAB仿真
electrolytic tellurium
genetic algorithm
BP neural network
MATLAB simulation
