摘要
针对电力市场环境中的两区域互联系统,研究了负荷频率控制的非线性、参数的不确定和纯迟延特性等问题,提出了一种基于模糊径向基函数神经网络的自适应控制器,即利用径向基函数神经网络进行自学习、修正与完善模糊规则,改善其动态性能。将Matlab与Labview软件相结合进行仿真,结果表明上述方法具有较强的自适应和自学习能力,将其应用于复杂的非线性电力系统的负荷频率控制中,取得了较好的控制效果。
Aiming at the two-area interconnected system, the nonlinearity, parameter uncertainty and pure time-delay characteristic of load frequency control are researched, then an adapative controller based on fuzzy radial basis function （RBF） neural netwrok is proposed, namely, by means of RBF neural network the self-learning, modification and improvement of fuzzy rules are conducted to improve dynamic performance of the adaptive controller. Combining Matlab software with Labview software, the simulation of the proposed adapative controller is carded out. Simulation results show that the proposed adapative controller possesses high adaptivitY and self-learning ability. Applying the proposed adaptive controller to load frequency control of complex nonlinear power system, a favorable control effect is obtained.
出处
《电网技术》
EI
CSCD
北大核心
2008年第12期64-69,共6页
Power System Technology
基金
新世纪优秀人才支持计划资助项目(NCET-06-0207)
北京市自然科学基金资助项目(4062030)。
