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Considering temperatures in operational planning of district heating systems
RISE Research Institutes of Sweden, Säkerhet och transport, Mätteknik.ORCID-id: 0000-0002-4173-1390
2023 (engelsk)Rapport (Annet vitenskapelig)
Abstract [en]

The project SeCoHeat aims at assessing the additional profits that district heating systems can make by participating in new electricity markets, such as ancillary service markets. A model has been developed to schedule district heating units on an hourly basis to minimize heat and electricity production costs while maximizing revenues from electricity markets. This model works with hourly energy flows. In this report, the importance of considering temperature quality in district heating networks when scheduling district heating units is investigated. Temperature quality refers to controlling mass flows and supply temperatures to ensure acceptable confort at the end-consumers. Traditional scheduling models use an energy-only formulation where energy is related to the product of temperaturate and mass flows. They do not consider these two quantities separately and, therefore, are unable to capture temperature quality aspects. On the other hand, these traditional scheduling models are less complex than a full representation of both temperatures and mass flows. Traditional scheduling models based on an energy-only formulation can be expressed as MILP optimization problems, whereas considering both temperatures and mass flows lead to MINLP optimization problems which are must harder to solve. Several simplications and reformulations have been proposed in this report to make the full MINLP problem less complex. These simplifications reduce the number of non-linear equations and, for one of them, even leads to a MILP formulation. In addition, a literature review about exisiting linear reformulations of the full MINLP problem and the importance of considering temperature quality is performed. This report gives a ground to further develop scheduling models that make tradeoffs between model complexity and accurate representation of temperature quality.

sted, utgiver, år, opplag, sider
2023. , s. 19
Serie
RISE Rapport ; 2023:19
HSV kategori
Identifikatorer
URN: urn:nbn:se:ri:diva-73116ISBN: 978-91-89821-64-4 (digital)OAI: oai:DiVA.org:ri-73116DiVA, id: diva2:1856930
Tilgjengelig fra: 2024-05-08 Laget: 2024-05-08 Sist oppdatert: 2024-05-08bibliografisk kontrollert

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Hamon, Camille

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