| 引用本文: | 殷桂梁,孙海宁,张志华.模糊神经网络光伏功率调节系统[J].电力自动化设备,2012,32(1): |
| YIN Guiliang,SUN Haining,ZHANG Zhihua.Photovoltaic power conditioning system based on fuzzy neural network[J].Electric Power Automation Equipment,2012,32(1): |
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| 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。 |
| 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 |
| DOI： |
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| Photovoltaic power conditioning system based on fuzzy neural network |
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YIN Guiliang, SUN Haining, ZHANG Zhihua
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Department of Electrical Engineering，Yanshan University，Qinhuangdao 066004，China
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| Abstract: |
| PVPCS（PhotoVoltaic Power Conditioning System） consists of photovoltaic 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. |
| Key words: photovoltaic cell grid-connection power conditioning harmonic analysis compensation fuzzy neural networks control reactive power |
