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| 摘要: |
| 统一潮流控制器UPFC(Unified Power Flow Controller)是现代电力系统中调节电压和潮流的有效手段。提出了一种由径向基函数神经网络RBFNN(Radial Basic Function Neuro-Network)和TS(Takagi-Sugeno)模糊控制策略综合而成的统一潮流控制器控制策略设计方案，即遗传神经模糊综合控制GNF(Genetic Neural Fuzzy)。利用TS模糊控制策略实时更新RBFNN参数，同时采用多机系统中的转速信号ITAE指数作为适应度函数。利用遗传算法GA(Genetic Algorithm)优化TS模糊控制策略系数以及辅助阻尼信号参数．提高了系统的暂态稳定性。经验证，该方案比传统的PI控制策略具有更好的系统振荡阻尼性能，改善了系统的动态品质。 |
| 关键词: GNF 统一潮流控制器 ITAE指数 TS模糊控制策略 遗传算法 |
| DOI： |
| 分类号:TM712 |
| 基金项目: |
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| Design of GNF scheme for UPFC |
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SUN Rong - fu CHEN Tie YANG Zhen - dong
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| Abstract: |
| UPFC ( Unified Power Flow Controller ) has been proved an effective means for regulating voltage and power flow in modern power systems.A GNF ( Genetic Neural Fuzzy ) scheme for UPFC is presented ,which integrates RBFNN ( Radial Basic Function Neuro - Network ) and TS - fuzzy schemes.TS - fuzzy scheme is used to real - timely refresh RBFNN parameters ,and GA ( Genetic Algorithm ) is used to optimize the factors of TS - fuzzy scheme and the parameters of auxiliary damping signal with the ITAE index of rotate speed signal in multi - machine system as adaptability function ,which improves the transient stability of power system.Case studies show that it has better damping performance than the conventional PI controller does and improves the system dynamic character. |
| Key words: GNF,UPFC,ITAE index,TS - fuzzy control,GA |
