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Formulation and assessment of multi-objective optimal sizing of district heating network.

Authors :
Merlet, Yannis
Baviere, Roland
Vasset, Nicolas
Source :
Energy. Aug2022, Vol. 252, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

The efficiency of a District Heating (DH) network depends among other things on the quality of its design and more precisely on the sizing of the distribution network pipes. Providing DH designers with relevant methodology to select appropriate pipes is crucial to maximize the utility of those systems. This paper presents a methodology focusing on the optimal sizing of pipe diameters in DH networks: the methodology uses a genetic algorithm to generate a set of Pareto-optimal sizing choices. An implementation of the methodology is presented, and is validated on three test cases, each of them corresponding to an elementary configuration, which can be encountered in real-world DH network. As a result, the performance of the results provided by the optimization for each test case are as good or better than the best reference solutions we could provide. The last part of this paper addresses the scalability of the proposed sizing methodology. The interest of the presented methodology is lies in the typology of optimal solutions provided for the test cases that could not be devised with traditional sizing methods and by the scalability of the method that makes it suitable for optimal sizing at city scale. • An optimal sizing methodology for the pipes of district heating networks is presented. • The methodology is based on multi-objective optimization and simulation. • A validation and verification workflow for optimal design of the distribution of district heating network is presented. • The methodology can tackle district heating networks up to 200 consumers. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
252
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
157048039
Full Text :
https://doi.org/10.1016/j.energy.2022.123997