A fast algorithm to computer the H∞ -norm of a transfer function matrix
Systems & Control Letters
N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
Modeling of future cyber-physical energy systems for distributed sensing and control
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Multi-time-scale analysis of a power system
Automatica (Journal of IFAC)
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The major subject of this paper is the introduction and testing of a new modeling paradigm necessary for enabling sustainable performance of electric energy systems. In previous work we have identified major challenges to systematically modeling distributed, non-uniform resources emerging in power grids. Today's modeling of electric energy systems is either entirely based on first principles which suffers significantly from the ever-increasing complexity of non-uniform devices, or is purely based on computer science data-driven approaches which lose the fundamental physical insights of electric power networks. Therefore, it is very difficult with today's modeling practices to integrate distributed non-uniform resources using both first-principle and data driven approaches in large-scale cyber-physical energy systems. In sharp contrast, this paper presents a holistic multi-scale modeling approach by combing advances from (1) physics based modeling of emerging distributed resources (e.g. wind generation and storage devices), and (2) data-driven modeling of load resources. With both physics-based models of distributed resources and data-driven models of flexible demands, key parameters are abstracted and identified from the detailed dynamical models necessary for the multi-scale power system operations. The proposed modeling framework is tested using realistic phasor measurement unit data obtained from Electric Reliability Council of Texas (ERCOT).