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Open AccessArticle

Formulation of Exergy Cost Analysis to Graph-Based Thermal Network Models

Department of Energy, Politecnico di Torino, Turin 10129, Italy
Department of Energy Systems and Environment, Ecole des Mines de Nantes, Nantes 44300, France
Department of Research and Innovation, Veolia VERI, Limay 78520, France
Author to whom correspondence should be addressed.
Academic Editor: Milivoje Kostic
Entropy 2017, 19(3), 109;
Received: 12 January 2017 / Accepted: 8 March 2017 / Published: 10 March 2017
(This article belongs to the Special Issue Thermoeconomics for Energy Efficiency)
Information from exergy cost analysis can be effectively used in the design and management of modern district heating networks (DHNs) since it allows to properly account for the irreversibilities in energy conversion and distribution. Nevertheless, this requires the development of suitable graph-based approaches that are able to effectively consider the network topology and the variations of the physical properties of the heating fluid on a time-dependent basis. In this work, a formulation of exergetic costs suitable for large graph-based networks is proposed, which is consistent with the principles of exergetic costing. In particular, the approach is more compact in comparison to straightforward approaches of exergetic cost formulation available in the literature, especially when applied to fluid networks. Moreover, the proposed formulation is specifically considering transient operating conditions, which is a crucial feature and a necessity for the analysis of future DHNs. Results show that transient effects of the thermodynamic behavior are not negligible for exergy cost analysis, while this work offers a coherent approach to quantify them. View Full-Text
Keywords: graph-based models; exergy; thermoeconomics; exergy costing; district heating graph-based models; exergy; thermoeconomics; exergy costing; district heating
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Coss, S.; Guelpa, E.; Letournel, E.; Le-Corre, O.; Verda, V. Formulation of Exergy Cost Analysis to Graph-Based Thermal Network Models. Entropy 2017, 19, 109.

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