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A Decentralized Functional Observer Based Optimal LFC Considering Unknown Inputs, Uncertainties, and Cyber-Attacks

This paper proposes a novel, unknown input functional observer based optimal load frequency control approach for real-world complex nonlinear power systems. In the proposed control approach, the control signal applied to each power plant is directly estimated via the well-designed functional observer. The proposed functional dynamic estimator is able to handle parametric and nonparametric uncertainties, control loop and sensor faults, unknown inputs, and cyber-attacks. The observer for each power plant is decoupled from the other plants resulting in a more feasible implementation, reducing the complexity of the estimator and improving the reliability of the proposed control system. The applicability of the proposed method is shown on IEEE 39 bus-system divided into three control areas. The effectiveness of the proposed control scheme is verified by comparing results with well-known control schemes. Tolerance of the proposed technique to unknown inputs, uncertainties, and possible cyber-attacks is verified by several simulation scenarios.
- Isfahan University of Technology Iran (Islamic Republic of)
- Isfahan University of Technology Iran (Islamic Republic of)
- National Technical University of Athens Greece
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).114 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
