Decompositions of injection patterns for nodal flow allocation in renewable electricity networks

TY - JOUR

T1 - Decompositions of injection patterns for nodal flow allocation in renewable electricity networks

AU - Schäfer, Mirko

AU - Tranberg, Bo

AU - Hempel, Sabrina

AU - Schramm, Stefan

AU - Greiner, Martin

PY - 2017/8/2

Y1 - 2017/8/2

N2 - The large-scale integration of fluctuating renewable power generation represents a challenge to the technical and economical design of a sustainable future electricity system. In this context, the increasing significance of long-range power transmission calls for innovative methods to understand the emerging complex flow patterns and to integrate price signals about the respective infrastructure needs into the energy market design. We introduce a decomposition method of injection patterns. Contrary to standard flow tracing approaches, it provides nodal allocations of link flows and costs in electricity networks by decomposing the network injection pattern into market-inspired elementary import/export building blocks. We apply the new approach to a simplified data-driven model of a European electricity grid with a high share of renewable wind and solar power generation.

AB - The large-scale integration of fluctuating renewable power generation represents a challenge to the technical and economical design of a sustainable future electricity system. In this context, the increasing significance of long-range power transmission calls for innovative methods to understand the emerging complex flow patterns and to integrate price signals about the respective infrastructure needs into the energy market design. We introduce a decomposition method of injection patterns. Contrary to standard flow tracing approaches, it provides nodal allocations of link flows and costs in electricity networks by decomposing the network injection pattern into market-inspired elementary import/export building blocks. We apply the new approach to a simplified data-driven model of a European electricity grid with a high share of renewable wind and solar power generation.

KW - Statistical and Nonlinear Physics

UR - http://www.scopus.com/inward/record.url?scp=85026630452&partnerID=8YFLogxK

U2 - 10.1140/epjb/e2017-80200-y

DO - 10.1140/epjb/e2017-80200-y

M3 - Journal article

SN - 1434-6028

VL - 90

SP - 1

EP - 11

JO - European Physical Journal B. Condensed Matter and Complex Systems

JF - European Physical Journal B. Condensed Matter and Complex Systems

IS - 8

M1 - 144

ER -