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Differential Evolution Algorithm Optimized Dual Mode Load Frequency Controller for Isolated Wind-Diesel Power System with SMES & Fuel Cell

机译:SMES&燃料电池隔离风柴油机系统优化的差分演进算法优化双模负载频率控制器

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摘要

Background: This paper presents dynamic performance analysis of isolated wind-diesel power system. A dual mode controller is proposed for pitch control of wind turbine generator. Methods: The parameters of the controller are optimized by Differential Evolution (DE) algorithm. The hybrid model was simulated with the proposed load frequency controller (LFC) by considering step load perturbation. The minimization of time multiplied integral of absolute error is considered as the objective function. The performance of the proposed controller is compared with the published result of the optimal controller. Further, the performance of the system is investigated by incorporating Super Conducting Magnetic Energy Storage (SMES) and Fuel Cell (FC). Also, the dynamic performance is investigated for changing step load perturbations. Furthermore, the response of the system is analyzed towards random loading. Results: Finally, sensitivity analysis is done by varying the system parameters and operating conditions from their nominal values. Conclusion: The simulation results show that the proposed dual mode DE optimized controller gives better transient and steady state response.
机译:背景:本文介绍了隔离风力柴油机动力系统的动态性能分析。提出了一种用于风力涡轮发电机的俯仰控制的双模式控制器。方法:控制器的参数通过差分演进(DE)算法进行了优化。通过考虑步骤负载扰动,用所提出的负载频率控制器(LFC)模拟混合模型。最小化绝对误差的时间乘以的积分被认为是目标函数。将所提出的控制器的性能与最佳控制器的公布结果进行比较。此外,通过结合超级导电磁能存储(SME)和燃料电池(FC)来研究系统的性能。此外,研究了动态性能以改变阶跃负载扰动。此外,分析了系统的响应朝向随机加载。结果:最后,通过从其标称值改变系统参数和操作条件来完成敏感性分析。结论:仿真结果表明,所提出的双模DE优化控制器提供更好的瞬态和稳态响应。

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