Frequency stability improvement of micro hydro power system using hybrid SMES and CES based on Cuckoo search algorithm

M. Djalal, H. Setiadi, A. Imran
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引用次数: 11

Abstract

Micro hydro has been chosen because it has advantages both economically, technically and as well as in terms of environmental friendliness. Micro hydro is suitable to be used in areas that difficult to be reached by the grid. Problems that often occur in the micro hydro system are not the constant rotation of the generator that caused by a change in load demand of the consumer. Thus causing frequency fluctuations in the system that can lead to damage both in the plant and in terms of consumer electrical appliances. The appropriate control technology should be taken to support the optimum performance of micro hydro. Therefore, this study will discuss a strategy of load frequency control by using Energy Storage. Superconducting magnetic energy storage (SMES) and capacitor energy storage (CES) are devices that can store energy in the form of a fast magnetic field in the superconducting coil. For the optimum performance, it is necessary to get the optimum tuning of SMES and CES parameters. The artificial intelligence methods, Cuckoo Search Algorithm (CSA) are used to obtain the optimum parameters in the micro hydro system. The simulation results show that the application of the CSA that use to tune the parameters of hybrid SMES-CES-PID can reduce overshoot oscillation of frequency response in micro hydro power plant.
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基于Cuckoo搜索算法的混合SMES和CES改进微水电系统频率稳定性
选择微型水力发电是因为它在经济、技术和环境友好方面都有优势。微型水电适用于电网难以到达的地区。在微型水电系统中经常出现的问题不是由于用户负荷需求的变化而引起的发电机不断旋转。从而引起系统的频率波动,从而导致工厂和消费电器的损坏。应采取适当的控制技术,以支持微水电的最佳性能。因此,本研究将探讨一种基于储能的负荷频率控制策略。超导磁能存储(SMES)和电容储能(CES)是在超导线圈中以快速磁场的形式存储能量的器件。为了获得最优的性能,有必要对SMES和CES参数进行最优调整。采用人工智能方法和布谷鸟搜索算法(CSA)来获得微水电系统的最优参数。仿真结果表明,应用CSA对混合型smb - ce - pid进行参数整定可以减小微水电厂频率响应的超调振荡。
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发文量
10
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