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Enabling inter-area reserve exchange through stable benefit allocation mechanisms

Karaca, Orcun
•
Delikaraoglou, Stefanos
•
Hug, Gabriela
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December 20, 2019

The establishment of a single European day-ahead market has accomplished the integration of the regional day-ahead markets. However, the reserves provision and activation remain an exclusive responsibility of regional operators. This limited spatial coordination and the sequential market structure hinder the efficient utilization of flexible generation and transmission, since their capacities have to be ex-ante allocated between energy and reserves. To promote reserve exchange, recent work has proposed a preemptive model that defines the optimal inter-area transmission capacities for energy and reserves reducing the expected system cost. This decision-support tool, formulated as a stochastic bilevel program, respects the current architecture but does not suggest area-specific costs that guarantee sufficient incentives for all areas to accept the proposed solution. To this end, we formulate a preemptive model in a framework that allows the application of coalitional game theory methods to obtain a stable benefit allocation, i.e., an outcome immune to coalitional deviations ensuring willingness of all areas to coordinate. We show that benefit allocation mechanisms can be formulated either at the day-ahead or the real-time stages, in order to distribute the expected or the scenario-specific benefits, respectively. For both games, the proposed benefits achieve minimal stability violation, while allowing for a tractable computation with limited queries to the bilevel program. Our case studies, based on an illustrative and a more realistic test case, compare our method with well-studied benefit allocations, namely, the Shapley value and the nucleolus. We show that our method performs better in stability, tractability, and fairness, which would potentially be dictated by a criterion chosen by the regulator.

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Type
report
Author(s)
Karaca, Orcun
Delikaraoglou, Stefanos
Hug, Gabriela
Kamgarpour, Maryam  
Date Issued

2019-12-20

Subjects

Mathematics - Optimization and Control

URL
http://arxiv.org/abs/1912.09933
Editorial or Peer reviewed

NON-REVIEWED

Written at

OTHER

EPFL units
SYCAMORE  
Available on Infoscience
December 1, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/183418
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