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Transient Performance Improvement of Power Systems Using Fuzzy Logic Controlled Capacitive-Bridge Type Fault Current Limiter

机译:模糊逻辑控制电容式故障电流限制器电力系统瞬态性能改进

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摘要

This paper proposes the novel application of a genetic algorithm optimized fuzzy logic controller as a nonlinear controller for capacitive bridge type fault current limiter (CBFCL) to improve the stability performance of the power systems. The proposed controller provides fast convergence for the system and uses data from the system as a feedback in the controller loops. The performance of the proposed genetic algorithm optimized fuzzy logic controlled CBFCL is compared with that of a static nonlinear controller based CBFCL and a static nonlinear controller-based bridge type fault current limiter (BFCL). The detail controller design and stability analysis are carried out on the IEEE 39 bus power system in MATLAB/SIMULINK. To capture a realistic system's response, a wind farm is connected to bus one in the IEEE 39 bus system. From the simulation results and several quantifying parameters, it is shown that the proposed genetic algorithm optimized fuzzy logic controlled CBFCL can effectively improve the stability and the performance of the power system as well as the grid connected wind farm. Further, the proposed controller performs better than the static nonlinear controller based CBFCL and the static nonlinear controller based BFCL.
机译:本文提出了一种遗传算法优化模糊逻辑控制器作为电容桥式故障电流限制器(CBFCL)的非线性控制器的新颖应用,以提高电力系统的稳定性性能。所提出的控制器为系统提供快速收敛,并使用系统中的数据作为控制器环中的反馈。将所提出的遗传算法优化模糊逻辑控制CBFCL的性能与基于静态非线性控制器的CBFCL和基于静态非线性控制器的桥式故障电流限制器(BFCL)进行了比较。详细控制器设计和稳定性分析在Matlab / Simulink中的IEEE 39总线电力系统上进行。为了捕获现实系统的响应,风电场连接到IEEE 39总线系统中的总线。从仿真结果和多种量化参数来看,所提出的遗传算法优化的模糊逻辑控制CBFCL可以有效地提高电力系统的稳定性和性能以及电网连接的风电场。此外,所提出的控制器比基于静态非线性控制器的CBFCL和基于静态非线性控制器的BFCL执行更好。

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