A Bicriteria Almost Equal Minimum Cost Flow Model for Day-Ahead Trading

E. Finhold, T. Heller (), S. O. Krumke and N. Leithäuser
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E. Finhold: Fraunhofer Institute for Industrial Mathematics, ITWM
T. Heller: Fraunhofer Institute for Industrial Mathematics, ITWM
S. O. Krumke: University of Kaiserslautern
N. Leithäuser: Fraunhofer Institute for Industrial Mathematics, ITWM

Chapter Chapter 22 in Operations Research Proceedings 2022, 2023, pp 181-187 from Springer

Abstract: Abstract As the share of renewable energy and therefore the fluctuation in power generation increases, using a battery to market the power saved/used by a flexible process becomes more and more important and attractive. The charging and discharging process of a battery can be modeled as a flow model in a time-expanded graph. We model the costs for this process as edge costs between nodes that correspond to consecutive points in time. An optimal battery strategy be obtained by computing a minimum cost flow in the given network. If the charging and discharging of a battery takes place as a coupled process of a production process, a steady and even charging and discharging is often important. In this paper, we describe a bicriteria flow model based on the Almost-Equal-Minimum Cost Flow Problem (AEMCFP) in which both trading profits and a steady flow of energy are considered as the two objectives. In the AEMCFP one is given additional sets of edges on which the flow values differ at most by a given constant. We obtain a strongly polynomial algorithm based on a parametric search approach. Furthermore, we present a case study for bidding on the German day ahead market.

Keywords: Network flows; Minimum cost flow; Parametric search; Energy trading (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-24907-5_22

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DOI: 10.1007/978-3-031-24907-5_22

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