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Model-Order Reduction (MOR) is an important technique that allows Reduced-Order Models (ROMs) of physical systems to be generated that can capture the dominant dynamics, but at lower cost than the full order system. One approach to MOR that has been successfully implemented in fluid dynamics is the Eigensystem Realization Algorithm (ERA). This method requires only minimal changes to the inputs and outputs of a CFD code so that the linear responses of the system to unit impulses on each input channel can be extracted. One of the challenges with the method is to specify the size of the input pulse. An inappropriate size may cause a failure of the code to converge due to non-physical behaviour arising during the solution process. This paper addresses this issue by using piston theory to estimate the appropriate input pulse size. [ABSTRACT FROM PUBLISHER]

This study proposes a novel synchrophasor measurement‐based correlation approach to identify the dominant oscillation modes in bulk power systems. In the proposed approach, the reference channel (RC) of cross‐correlation (CC) is optimally selected based on residue analysis. With the selected RC, the CC of field‐measurement data is formed to extract the free‐decay system responses. Then, eigensystem realisation algorithm (ERA) is applied to the extracted responses to estimate the system state‐space model. A practical model order selection strategy for ERA is proposed to determine the system model order. Further, cross‐coherence spectrum is employed to distinguish the dominant modes from the eigenvalues of the estimated state‐space model. The proposed method can achieve accurate and robust solutions in the presence of different levels of errors and noises in measurement data. The effectiveness of the proposed method has been verified in a 16‐generator, 68‐bus test system as well as the China Southern Power Grid system. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hierarchical optimal control framework to support frequency and voltage in multi-area transmission systems, integrating battery energy storage systems (BESSs). The design is based on the coordinated active and reactive power injection from the BESSs over conventional synchronous generator-based control for fast and timely mitigation of voltage and frequency deviations. The principle of this new idea is to use two hierarchical schemes, one physical and one logical. The objective of the first scheme prioritises the power injection from the BESSs installed in the area where a contingency occurs, consequently reducing the disturbance of the dynamics in the neighbouring areas. In the second scheme, operational rules for aggregated BESSs in each are incorporated, increasing the safety of the asset. The proposed approach exploits the advantages of time-synchronised measurements, the eigensystem realisation algorithm (ERA) identification technique, the optimal linear quadratic Gaussian (LQG) controllers and a new aggregating agent that coordinates the power injection of BESSs in a hierarchical and scalable scheme to precisely regulate frequency and voltage of modern transmission grids, increasing their reliability and stability. The feasibility and robustness of the proposal is demonstrated using simulated scenarios with significant load changes and three-phase, three-cycle faults on a modified Kundur-system with four interconnected areas, mitigating frequency and voltage contingencies in less than 450 ms. • Real-time, optimal and hierarchical controller provides voltage and frequency support. • Optimal power injection by smartly clustered BESSs mitigates power supply imbalances. • The aggregator agent adds smart logical functions for information handling. • The real-time controller regulates voltage and frequency deviations in 450 ms. • The proposed control approach works under large load changes and failures. [ABSTRACT FROM AUTHOR]