Discrete-time prediction based event-triggered controller design: An application to networked multi-area power system with time delays

IF 1.8 Q3 AUTOMATION & CONTROL SYSTEMS IFAC Journal of Systems and Control Pub Date : 2023-09-01 DOI:10.1016/j.ifacsc.2023.100220
Sumant Anand , Manjeet Kumar , Sanjeev Kumar , Arkdev
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Abstract

This work proposes a solution for power system stability by utilizing prediction-based event-triggered control (ETC) in the discrete-time domain. The proposed control method can handle a large sampling period, and the event-triggered mechanism (ETM) is applied in both controller and actuator loops to reduce the network’s computational and communication burden. Input and output (I/O) quantizers are used to avoid the quantization error that arises due to sampling and are also included in the stability analysis. The proposed control strategy is evaluated under various load scenarios using three-area interconnected power systems. The results demonstrate that the proposed approach saves 25.5%, 22%, and 23.5% of channel bandwidth in each area, as compared to the conventional time-triggered control approach. A comparative study shows that the proposed work outperforms recently reported works in terms of better event triggering number, average inter-event time, and performance indices. The effectiveness of the proposed control schemes is further validated by considering uncertainty in system parameters and typical power system nonlinearities. The study also illustrates the integration of renewable energy resources (RERs) and electric vehicles (EVs). The closed-loop system stability is proved theoretically using uniform ultimate boundedness and validated through simulations in MATLAB R2018a.

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基于离散时间预测的事件触发控制器设计:在具有时滞的网络化多区域电力系统中的应用
本文提出了一种在离散时间域中利用基于预测的事件触发控制(ETC)来解决电力系统稳定性问题的方法。所提出的控制方法可以处理大采样周期,并且在控制器和执行器回路中都采用了事件触发机制(ETM),以减少网络的计算和通信负担。输入和输出(I/O)量化器用于避免由于采样而产生的量化误差,并且也包含在稳定性分析中。利用三区互联电力系统,对所提出的控制策略在不同负荷情况下进行了评估。结果表明,与传统的时间触发控制方法相比,该方法在每个区域分别节省了25.5%、22%和23.5%的信道带宽。一项比较研究表明,本文在事件触发次数、平均事件间时间和性能指标方面优于近期报道的作品。通过考虑系统参数的不确定性和典型的电力系统非线性,进一步验证了所提控制方案的有效性。该研究还说明了可再生能源(res)和电动汽车(ev)的整合。利用均匀极限有界性理论证明了闭环系统的稳定性,并在MATLAB R2018a中进行了仿真验证。
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来源期刊
IFAC Journal of Systems and Control
IFAC Journal of Systems and Control AUTOMATION & CONTROL SYSTEMS-
CiteScore
3.70
自引率
5.30%
发文量
17
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