摘要
光伏功率调节系统(PVPCS)集光伏并网发电与无功补偿为一体,以此来提高电能质量和减少电网功率损耗。在分析了系统的工作原理和控制策略的基础上,提出了基于模糊神经网络(FNN)的智能控制策略,构成了具有双FNN模型结构的光伏功率调节系统,能够稳定直流侧电容电压,优化对电网谐波、无功的补偿效果,而且具有更强的鲁棒性和适应性。仿真结果在调整系统功率的同时使谐波含量从4.61%下降到4.18%,证实了所提策略的可行性。
PVPCS （PhotoVohaic Power Conditioning System） consists of photovohaic power generation and var ＆ harmonic compensation to improve power quality and reduce network loss. Its working principle and control strategy are analyzed and an intelligent control strategy based on FNN（Fuzzy Neural Network） is proposed to build the PVPCS with the structure of dual FNN models,which optimizes the var ＆ harmonic compensation while stabilizes the DC capacitor voltage,with better robustness and adaptability. The simulative results show that the harmonic content is reduced from 4.61% to 4.18 % during system power conditioning,which proves its feasibility.
出处
《电力自动化设备》
EI
CSCD
北大核心
2012年第1期24-28,共5页
Electric Power Automation Equipment
关键词
光伏电池
并网
功率调节
谐波分析
补偿
模糊神经网络
控制
无功功率
photovoltaic cell
grid-connection
power conditioning
harmonic analysis
compensation
fuzzy neural networks
eontrol
reactive power
