2021
DOI: 10.1002/rnc.5465
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Dynamic event‐triggered H load frequency control for multi‐area power systems with communication delays

Abstract: This paper investigates dynamic event‐triggered H∞ load frequency control for multi‐area power systems with communication delays. A novel co‐design method of trigger parameters and H∞ controller based on output feedback is proposed. Unlike routine multiplication operations, this method eliminates rank constraints on the input and output matrices, and avoids the processing of nonlinear terms related to the trigger parameters. Furthermore, under the presented dynamic event‐triggered mechanism, the threshold para… Show more

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Cited by 14 publications
(6 citation statements)
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“…The multi-area LFC power systems of the i th area are shown in Figure 1 and the parameters are listed in Table 1. 24 Area control error (ACE) is used to measure the tie-line switching power between control areas. AC E i signal is a linear combination of frequency deviation and tie-line power deviation of i th area, which can be defined as…”
Section: Problem Formulationmentioning
confidence: 99%
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“…The multi-area LFC power systems of the i th area are shown in Figure 1 and the parameters are listed in Table 1. 24 Area control error (ACE) is used to measure the tie-line switching power between control areas. AC E i signal is a linear combination of frequency deviation and tie-line power deviation of i th area, which can be defined as…”
Section: Problem Formulationmentioning
confidence: 99%
“…The robust stability and stabilization of adaptive event-triggered LFC of multi-area power systems were investigated under a networked environment via sliding mode control in Lv et al 23 Li et.al. 24 investigated dynamic event-triggered H ∞ LFC for multi-area power systems with communication delays. Hu et al 25 proposed intermittent communication consensus control based on dynamic event triggering mechanism for leaderless directed MAS networks.…”
Section: Introductionmentioning
confidence: 99%
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“…Briefly, the LSISs contain several subsystems which are interconnected to each other and their communications make the system exhibit complex dynamical behaviors. [1][2][3][4][5] In order to study those behaviors, various types of analysis such as stability analysis, bifurcation analysis, control algorithms (stabilization analysis), analysis of controllability and observability are performed to better understand the nature of LSISs and develop the further application process of LSISs. On the other hand, the state variables are often not available in real-world LSISs, in this regard, an observer-based system is designed under a decentralized control technique that has the ability to mimic the original structure or measure the original state, which relies on only the local measurement information and may reduce the computational complexity, and improve the consistency and robustness.…”
Section: Introductionmentioning
confidence: 99%