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Journal article

Optimal allocation of HVDC interconnections for exchange of energy and reserve capacity services

From

Swiss Federal Institute of Technology Zurich1

Department of Electrical Engineering, Technical University of Denmark2

Energy Analytics and Markets, Center for Electric Power and Energy, Centers, Technical University of Denmark3

Center for Electric Power and Energy, Centers, Technical University of Denmark4

The increasing shares of stochastic renewables bring higher uncertainty in power system operation and underline the need for optimal utilization of flexibility. However, the European market structure that separates energy and reserve capacity trading is prone to inefficient utilization of flexible assets, such as the HVDC interconnections, since their capacity has to be ex-ante allocated between these services.

Stochastic programming models that co-optimize day-ahead energy schedules with reserve procurement and dispatch, provide endogenously the optimal transmission allocation in terms of minimum expected system cost. However, this perfect temporal coordination of trading floors cannot be attained in practice under the existing market design.

To this end, we propose a decision-support tool that enables an implicit temporal coupling of the different trading floors using as control parameters the inter-regional transmission capacity allocation between energy and reserves and the area reserve requirements. The proposed method is formulated as a stochastic bilevel program and cast as mixed-integer linear programming problem, which can be efficiently solved using a Benders decomposition approach that improves computational tractability.

This model bears the anticipativity features of a transmission allocation model based on a pure stochastic programming formulation, while being compatible with the current market structure. Our analysis shows that the proposed mechanism reduces the expected system cost and thus can facilitate the large-scale integration of intermittent renewables.

Language: English
Publisher: Springer Berlin Heidelberg
Year: 2019
Pages: 635-675
Journal subtitle: Optimization, Modeling, Simulation, and Economic Aspects
ISSN: 18683975 and 18683967
Types: Journal article
DOI: 10.1007/s12667-018-0288-6
ORCIDs: Pinson, Pierre and 0000-0003-0724-9477

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