Model Reduction of Nonlinear Systems by Trajectory Piecewise Linear Based on Output-Weighting Models: A Balanced-Truncation Methodology

Mohseni, Seyed Saleh; Yazdanpanah, Mohammad Javad; Noei, Abolfazl Ranjbar

doi:10.1007/s40998-018-0058-4

Cited by 2 publications

(1 citation statement)

References 14 publications

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Order By: Relevance

“…The dynamical system describing the reliability of the network is simplified by first calculating its Hankel singular values (HSVs) [11], which indicate the relevance of each system state in terms of reliability, and then the dynamics which have a smaller impact on the considered reliability indexes are neglected. Model Reduction has already been applied in various power system analyses: MOR using balanced empirical Gramians was investigated for linear systems in [12,13,14] and nonlinear systems in [15,16,17,18,19]. Given the need to reduce large power systems, [20] used a linear system reduction method and the work was successful for small-signal stability while [21] performed a parametric MOR aimed at preserving parameters related to decentralised power system devices such as stabilisers.…”

Section: Network Reduction In Power System Analysis -Related Workmentioning

confidence: 99%

Model order reduction for reliability assessment of flexible power networks

Ndawula

Hernando‐Gil

et al. 2021

International Journal of Electrical Power & Energy Systems

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Model order reduction (MOR) has demonstrated its robustness and wide applicability in simulating large-scale mathematical models in the engineering research domain. In this paper, MOR techniques are applied to quantify relevant reliability metrics of power distribution systems and the impact associated with the integration of different smart grid technologies. To the best of the authors' knowledge, this is the first application of MOR techniques of balanced truncation to derive reliability models of electricity networks, which exhibit a reduced number of equivalent components and thus simplify the complexity for network analysis. The extensive case studies presented, based on both radial and meshed systems, demonstrate that the proposed technique allows for a faster reliability assessment through Monte Carlo simulation while preserving high accuracy. The proposed methodology can also be applied to systems endowed with photovoltaic and energy storage technologies, emphasising that this approach represents a promising starting point for reliability analysis of more complex systems, which are normally characterised by a large penetration of these distributed energy resources.

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