Model reduction for fast assessment of grid impact of high penetration PV

Jiang, Yazhou; Acharya, Naresh; Pan, Yan

doi:10.1109/isap.2017.8071384

Cited by 9 publications

(9 citation statements)

References 3 publications

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“…Typical applications of this approach include symmetrical or asymmetrical short circuit calculations and load flow calculations. In these cases, the performance of the reduced networks representations is evaluated in terms of accuracy of the power flow results with respect to the (more complex) initial model [8].…”

Section: Network Reduction In Power System Analysis -Related Workmentioning

confidence: 99%

“…The reduced-order system is then determined according to (5)- (8). In this specific case, the error bound of the model order reduction can be derived on the quadratic norm of the output.…”

Section: Model Order Reduction Of Systems Without Inputsmentioning

confidence: 99%

“…For this study, the removed system state is the one representing the probability of all PCs being in the UP state. The next step is to determine the transformation matrix T using (10) and then truncating (7) according to (8). This allows for a model reduction of the reduced form of the matrix A (which is full rank) from order n − 1 to r − 1.…”

Section: Calculation Of the Reduced-order Modelmentioning

confidence: 99%

“…Recalling that this system has no input, the transformation matrix T for the change of coordinates in the original system is obtained using (10) instead of (6). The reduced-order system (2) is then determined by truncating system (5) according to ( 7)- (8). For a certain order r of the reduced model, the corresponding error bound on the output (i.e.…”

Section: Illustration Of Mor Functionalitymentioning

confidence: 99%

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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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Section: Network Reduction In Power System Analysis -Related Workmentioning

confidence: 99%

“…The reduced-order system is then determined according to (5)- (8). In this specific case, the error bound of the model order reduction can be derived on the quadratic norm of the output.…”

Section: Model Order Reduction Of Systems Without Inputsmentioning

confidence: 99%

Section: Calculation Of the Reduced-order Modelmentioning

confidence: 99%

Section: Illustration Of Mor Functionalitymentioning

confidence: 99%

See 2 more Smart Citations

Model order reduction for reliability assessment of flexible power networks

Ndawula

Hernando‐Gil

et al. 2021

International Journal of Electrical Power & Energy Systems

View full text Add to dashboard Cite

show abstract

“…The proposed model reduction method retains the essential circuit elements, such as LTCs, voltage regulators etc. More detail on the model reduction tool can be seen in [21]. While this optional approach is part of CReST‐VCT frame work, it has not been used in the simulation results reported in this study.…”

Section: Crest‐vct Model Developmentmentioning

confidence: 99%