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Distributionally robust day-ahead combined heat and power plants scheduling with Wasserstein Metric
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems. Tech Univ Denmark DTU, Ctr Elect Power & Energy, Dept Elect Engn, DK-2800 Lyngby, Denmark..ORCID iD: 0000-0003-1267-0610
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0001-6000-9363
Tsinghua Univ, Tsinghua Berkeley Shenzhen Inst, Tsinghua Shenzhen Int Grad Sch, Shenzhen 518055, Peoples R China..ORCID iD: 0000-0001-7935-2567
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0002-8189-2420
2023 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 269, article id 126793Article in journal (Refereed) Published
Abstract [en]

Combined heat and power (CHP) plants are main generation units in district heating systems that produce both heat and electric power simultaneously. Moreover, CHP plants can participate in electricity markets, selling and buying the extra power when profitable. However, operational decisions have to be made with unknown electricity prices. The distribution of unknown electricity prices is also not known exactly and uncertain in practice. Therefore, the need of tools to schedule CHP units' production under distributional uncertainty is necessary for CHP producers. On top of that, a heating network could serve as a heat storage and an additional source of flexibility for CHP plants. In this paper, a distributionally robust short-term operational model of CHP plants in the day-ahead electricity market is developed. The model accounts for the heating network and considers temperature dynamics in the pipes. The problem is formulated in a data-driven manner, where the production decisions explicitly depend on the historical data for the uncertain day-ahead electricity prices. A case study is performed, and the resulting profit of the CHP producer is analyzed. The proposed operational strategy shows high reliability in the out-of-sample performance and a profit gain of the CHP producer, who is aware of the temperature dynamics in the heating network.

Place, publisher, year, edition, pages
Elsevier BV , 2023. Vol. 269, article id 126793
Keywords [en]
Stochastic programming, Combined heat and power, District heating, Distributionally robust optimization, Electricity markets
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-326451DOI: 10.1016/j.energy.2023.126793ISI: 000963159700001Scopus ID: 2-s2.0-85147214520OAI: oai:DiVA.org:kth-326451DiVA, id: diva2:1754203
Note

QC 20230503

Available from: 2023-05-03 Created: 2023-05-03 Last updated: 2023-05-03Bibliographically approved

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Skalyga, MikhailAmelin, MikaelSöder, Lennart

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