Optimal operation of large district heating networks through fast fluid-dynamic simulation

Guelpa, Elisa; Toro, Claudia; Sciacovelli, Adriano; Melli, Roberto; Sciubba, Enrico

doi:10.1016/j.energy.2016.02.058

Cited by 108 publications

(46 citation statements)

References 15 publications

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“…This is the same numerical scheme that is adopted for calculating temperature distributions in the network [14], while here it is extended to the exergetic costs. In general, the exergetic flow at the control volume boundary between node and its upstream node is a function of the mass flow rate in the branch crossing the control volume and the temperature and pressure of the upstream node and respectively.…”

Section: Control Volume Definition and Exergetic Analysismentioning

confidence: 99%

Section: Control Volume Definition and Exergetic Analysismentioning

confidence: 99%

“…Nevertheless, this work focuses on the results that can be obtained by a thermo-fluid dynamic approach developed in [14], which is particularly suitable to effectively model transient operations in large networks with multiple loops. It must be noted that, in transient operation, both the thermodynamic properties and the directions of the hot water flow can change in time, which implies the calculation of time-dependent network properties.…”

Section: Control Volume Definition and Exergetic Analysismentioning

confidence: 99%

“…The case-study data is taken from previous projects, previously analyzed in [14], which have analyzed the thermo-fluidynamic behavior of the network. The lengths of the branches shown in Figure 3 are proportional to their real lengths in the network.…”

Section: Case Study: Example Thermal Heat Networkmentioning

confidence: 99%

“…Furthermore, thermal energy systems like DHNs can also be modeled through graph networks, where the two fundamental properties, nodes and branches, are used to represent the thermo-fluid dynamic properties of the system [14,17]. Considering Figure 1a, a general graph network consists of nodes connected by branches.…”

Section: Graph-based Thermal Networkmentioning

confidence: 99%

See 4 more Smart Citations

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

Coss

Guelpa

Letournel

et al. 2017

Entropy

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Abstract: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.

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Section: Control Volume Definition and Exergetic Analysismentioning

confidence: 99%

Section: Control Volume Definition and Exergetic Analysismentioning

confidence: 99%

Section: Control Volume Definition and Exergetic Analysismentioning

confidence: 99%

Section: Case Study: Example Thermal Heat Networkmentioning

confidence: 99%

Section: Graph-based Thermal Networkmentioning

confidence: 99%

See 3 more Smart Citations

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

Coss

Guelpa

Letournel

et al. 2017

Entropy

Self Cite

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Optimal control of district heating networks using a reduced order model

Rein

Möhring

Damm

et al. 2020

Optim Control Appl Methods

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SummaryWe study the optimal control of district heating networks using a reduced order model based on a system theoretic description close to the underlying Euler equations. In the presented scenarios, the central task is to limit the maximal feed‐in power occurring as a product of control and state variables. The underlying dynamics of heating networks acting as optimization constraints pose the central computational complexity, prohibiting the determination of an optimal control online. The advection of the injected energy density on the network results in an index‐1, quadratic in state differential algebraic equation, challenging to reduce. The suggested reduced model decreases the computation time of the optimization significantly. The effectiveness of the presented approach is demonstrated for an existing, large‐scale heating network including changes of flux directions.

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