The Technology of Suppressing Harmonics with Complex Neural Network is Applied to Microgrid

2017 International Symposium on Application of Materials Science and Energy Materials

材料科学;能源学

Zhang, Jing^1 ; Li, Zhan-Ying^1 ; Wang, Yan-Ping^1 ; Li, Yang^1 ; Zong, Ke-Yong^1

School of Information Science and Engineering, Dalian Polytechnic University, Dalian

116034, China^1

关键词: Complex neural networks;    Delay Time;    Dynamic tracking;    Ip-iq methods;    Micro grid;    Power supply current;    RBF Neural Network;    Simulation in matlabs;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/322/7/072031/pdf
DOI  :  10.1088/1757-899X/322/7/072031

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

According to the traits of harmonics in microgrid, a new CANN controller which combines BP and RBF neural network is proposed to control APF to detect and suppress harmonics. This controller has the function of current prediction. By simulation in Matlab / Simulink, this design can shorten the delay time nearly 0.02s (a power supply current cycle) in comparison with the traditional controller based on ip-iq method. The new controller also has higher compensation accuracy and better dynamic tracking traits, it can greatly suppress the harmonics and improve the power quality.