Distributed Energy Resource Benchmark Models for Quasi- Static Time-Series Power Flow Simulations

Jason Taylor; Jouni Peppanen; Josh Snodgrass; Denis Mende; Thomas I. Strasser; Mark McGranaghan; Daniel Fonseca; Shengen Chen; Markus Kraiczy; Alex Baitch

Distributed Energy Resource Benchmark Models for Quasi- Static Time-Series Power Flow Simulations

Jason Taylor, Jouni Peppanen, Josh Snodgrass, Denis Mende, Thomas I. Strasser, Mark McGranaghan, Daniel Fonseca, Shengen Chen, Markus Kraiczy, Alex Baitch

Publikation: Bücher und Berichte › Bericht

Abstract

The rapid evolution of DER technologies and applications poses a challenge when modelling these technologies - including inconsistent terminology as well as multiple representations of specific DER types. This technical brochure documents a DER benchmark model framework and a set of initial benchmark models for quasi-static time-series (QSTS) power flow simulations, which are intended as a common reference to understand and verify the performance of existing models as well as support standardization in industry models.

Originalsprache	Englisch
Erscheinungsort	Paris, France
Verlag	CIGRE
Seitenumfang	80
Band	906
ISBN (elektronisch)	978-2-85873-611-9
Publikationsstatus	Veröffentlicht - Juni 2023

Research Field

Power System Digitalisation
Power System Planning and Operation

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

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Taylor, J., Peppanen, J., Snodgrass, J., Mende, D., Strasser, T. I., McGranaghan, M., Fonseca, D., Chen, S., Kraiczy, M., & Baitch, A. (2023). Distributed Energy Resource Benchmark Models for Quasi- Static Time-Series Power Flow Simulations. CIGRE. https://e-cigre.org/publication/906-distributed-energy-resource-benchmark-models-for-quasi-static-time-series-power-flow-simulations

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keywords = "distributed energy resource, benchmark model, simulation, power flow analysis, quasi-static, time-series",

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Taylor, J, Peppanen, J, Snodgrass, J, Mende, D, Strasser, TI, McGranaghan, M, Fonseca, D, Chen, S, Kraiczy, M & Baitch, A 2023, Distributed Energy Resource Benchmark Models for Quasi- Static Time-Series Power Flow Simulations. Bd. 906, CIGRE, Paris, France. <https://e-cigre.org/publication/906-distributed-energy-resource-benchmark-models-for-quasi-static-time-series-power-flow-simulations>

TY - BOOK

T1 - Distributed Energy Resource Benchmark Models for Quasi- Static Time-Series Power Flow Simulations

AU - Taylor, Jason

AU - Peppanen, Jouni

AU - Snodgrass, Josh

AU - Mende, Denis

AU - Strasser, Thomas I.

AU - McGranaghan, Mark

AU - Fonseca, Daniel

AU - Chen, Shengen

AU - Kraiczy, Markus

AU - Baitch, Alex

PY - 2023/6

Y1 - 2023/6

N2 - The rapid evolution of DER technologies and applications poses a challenge when modelling these technologies - including inconsistent terminology as well as multiple representations of specific DER types. This technical brochure documents a DER benchmark model framework and a set of initial benchmark models for quasi-static time-series (QSTS) power flow simulations, which are intended as a common reference to understand and verify the performance of existing models as well as support standardization in industry models.

AB - The rapid evolution of DER technologies and applications poses a challenge when modelling these technologies - including inconsistent terminology as well as multiple representations of specific DER types. This technical brochure documents a DER benchmark model framework and a set of initial benchmark models for quasi-static time-series (QSTS) power flow simulations, which are intended as a common reference to understand and verify the performance of existing models as well as support standardization in industry models.

KW - distributed energy resource

KW - benchmark model

KW - simulation

KW - power flow analysis

KW - quasi-static

KW - time-series

M3 - Report

VL - 906

BT - Distributed Energy Resource Benchmark Models for Quasi- Static Time-Series Power Flow Simulations

PB - CIGRE

CY - Paris, France

ER -

Distributed Energy Resource Benchmark Models for Quasi- Static Time-Series Power Flow Simulations

Abstract

Research Field

UN SDGs

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