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Equilibrium optimizer‐tuned cascade fractional‐order 3DOF‐PID controller in load frequency control of power system having renewable energy resource integrated
International Transactions on Electrical Energy Systems ( IF 2.3 ) Pub Date : 2020-11-11 , DOI: 10.1002/2050-7038.12702
Dipayan Guha 1 , Provas K. Roy 2 , Subrata Banerjee 3
Affiliation  

This paper suggests a novel cascade fractional‐order controller (CC‐FOC) comprising of three degrees of freedom proportional‐integral‐derivative (3DOF‐PID) and tilt‐integral‐derivative (TID) controllers for solving the load frequency control problem of an interconnected power system integrated with DFIG‐driven wind power system. In the proposed CC‐FOC, 3DOF‐PID and TID controllers are used as slave and master controllers, respectively, to alleviate system oscillations and to improve system stability in the wake of sudden perturbations. A novel meta‐heuristic technique, namely equilibrium optimizer (EO), has been adopted and successfully implemented for concurrent tuning of the proposed controller's different parameters. Simulation outcomes of the EO have been evaluated with those attained by gravitational search algorithm, grey wolf optimization, and the results are reported in the literature. The efficacy of the proposed CC‐FOC is established by contrasting its responses with the outcomes of 3DOF‐PID, 2DOF‐PID, TID, and conventional controllers. The mastery of the proposed controller is further assessed, including system nonlinearities like GRC and GDB. The results obtained through extensive simulation reveals that the suggested approach significantly enhances system performance compared to the prevalent controllers of the existing literature. Finally, the robustness of the test system having CC‐FOC integrated is demonstrated against wide variation in system parameters by employing Kharitonov's theorem.

中文翻译:

具有集成可再生能源的电力系统负载频率控制中的均衡优化器优化的级联分数阶3DOF-PID控制器

本文提出了一种新颖的级联分数阶控制器(CC-FOC),该控制器包含三个自由度比例积分微分(3DOF-PID)和倾斜积分微分(TID)控制器,用于解决电动机的负载频率控制问题。与DFIG驱动的风力发电系统集成的互连电力系统。在拟议的CC‐FOC中,将3DOF‐PID和TID控制器分别用作从属控制器和主控制器,以减轻系统振荡并在突然发生扰动后提高系统稳定性。已经采用了一种新颖的元启发式技术,即均衡优化器(EO),并成功实现了对建议控制器的不同参数的并发调整。EO的模拟结果已经通过重力搜索算法获得了评估,灰狼优化,其结果已在文献中报道。通过将CC-FOC的响应与3DOF-PID,2DOF-PID,TID和常规控制器的结果进行对比,可以确定CC-FOC的有效性。进一步评估了所提出的控制器的掌握程度,包括系统非线性,例如GRC和GDB。通过广泛的仿真获得的结果表明,与现有文献中流行的控制器相比,该方法可以显着提高系统性能。最后,通过使用Kharitonov定理,证明了集成了CC-FOC的测试系统的鲁棒性,以抵抗系统参数的广泛变化。2DOF‐PID,TID和常规控制器。进一步评估了所提出的控制器的掌握程度,包括系统非线性,例如GRC和GDB。通过广泛的仿真获得的结果表明,与现有文献中流行的控制器相比,该方法可以显着提高系统性能。最后,通过使用Kharitonov定理,证明了集成了CC-FOC的测试系统的鲁棒性,以抵抗系统参数的广泛变化。2DOF‐PID,TID和常规控制器。进一步评估了所提出的控制器的掌握程度,包括系统非线性,例如GRC和GDB。通过广泛的仿真获得的结果表明,与现有文献中流行的控制器相比,该方法可以显着提高系统性能。最后,通过使用Kharitonov定理,证明了集成了CC-FOC的测试系统的鲁棒性,以抵抗系统参数的广泛变化。通过广泛的仿真获得的结果表明,与现有文献中流行的控制器相比,该方法可以显着提高系统性能。最后,通过使用Kharitonov定理,证明了集成了CC-FOC的测试系统的鲁棒性,以抵抗系统参数的广泛变化。通过广泛的仿真获得的结果表明,与现有文献中流行的控制器相比,该方法可以显着提高系统性能。最后,通过使用Kharitonov定理,证明了集成了CC-FOC的测试系统的鲁棒性,以抵抗系统参数的广泛变化。
更新日期:2021-01-12
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