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Appl. Sci. 2017, 7(5), 488; doi:10.3390/app7050488

Design Optimization of a District Heating Network Expansion, a Case Study for the Town of Kiruna

Division of Energy Science, Energy Engineering, Department of Engineering Science and Mathematics, Luleå University of Technology, 971 87 Luleå, Sweden
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Academic Editors: Francesco Melino and Lisa Branchini
Received: 28 March 2017 / Revised: 2 May 2017 / Accepted: 5 May 2017 / Published: 10 May 2017
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Abstract

The urbanization of new areas beyond the existing perimeter of a town implies the expansion of several infrastructures, including the district heating network. The main variables involved in the design of the district heating network expansion are the layout of the new pipes, their diameters, and the capacity of the new heat production sites that are required to satisfy the increased demand of room heating and hot tap water. In this paper, a multi-objective evolutionary algorithm is applied to the minimization of the costs related to the expansion of the district heating network of the town of Kiruna, in northern Sweden. The results show that the spectrum of the optimal design compromises between investment costs for the new pipes and the new heat generation site on one side, and operating costs due to overall fuel consumption and pumping power in the network on the other. The presented methodology is a tool meant for the decision makers in the company who own the district heating network, to evaluate all the possible best design alternatives before making a decision. View Full-Text
Keywords: multi-objective optimization; network structure; complex network; district heating multi-objective optimization; network structure; complex network; district heating
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Vesterlund, M.; Toffolo, A. Design Optimization of a District Heating Network Expansion, a Case Study for the Town of Kiruna. Appl. Sci. 2017, 7, 488.

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