District Heating Network Design and Configuration Optimization with Genetic Algorithm

In this paper, the configuration of a district heating network which connects from the heating plant to the end users is optimized. Each end user in the network represents a building block. The connections between the heat generation plant and the end users are represented with mixed integer...

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Main Authors: Hongwei Li, Svend Svendsen
Format: Article
Language:English
Published: SDEWES Centre 2013-12-01
Series:Journal of Sustainable Development of Energy, Water and Environment Systems
Subjects:
Online Access: http://www.sdewes.org/jsdewes/pi2013.01.0022
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spelling doaj-5af55f521a9848d487df89ce7f7907822020-11-24T23:47:19ZengSDEWES CentreJournal of Sustainable Development of Energy, Water and Environment Systems1848-92572013-12-011429130310.13044/j.sdewes.2013.01.002200022District Heating Network Design and Configuration Optimization with Genetic AlgorithmHongwei Li0Svend Svendsen1 Civil Engineering Department, Technical University of Denmark, Lyngby, Denmark Civil Engineering Department, Technical University of Denmark, Lyngby, Denmark In this paper, the configuration of a district heating network which connects from the heating plant to the end users is optimized. Each end user in the network represents a building block. The connections between the heat generation plant and the end users are represented with mixed integer and the pipe friction and heat loss formulations are non-linear. In order to find the optimal district heating network configuration, genetic algorithm which handles the mixed integer nonlinear programming problem is chosen. The network configuration is represented with binary and integer encoding and is optimized in terms of the net present cost. The optimization results indicates that the optimal DH network configuration is determined by multiple factors such as the consumer heating load, the distance between the heating plant to the consumer, the design criteria regarding the pressure and temperature limitation, as well as the corresponding network heat loss. http://www.sdewes.org/jsdewes/pi2013.01.0022 District Heating NetworkOptimizationGenetic Algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Hongwei Li
Svend Svendsen
spellingShingle Hongwei Li
Svend Svendsen
District Heating Network Design and Configuration Optimization with Genetic Algorithm
Journal of Sustainable Development of Energy, Water and Environment Systems
District Heating Network
Optimization
Genetic Algorithm
author_facet Hongwei Li
Svend Svendsen
author_sort Hongwei Li
title District Heating Network Design and Configuration Optimization with Genetic Algorithm
title_short District Heating Network Design and Configuration Optimization with Genetic Algorithm
title_full District Heating Network Design and Configuration Optimization with Genetic Algorithm
title_fullStr District Heating Network Design and Configuration Optimization with Genetic Algorithm
title_full_unstemmed District Heating Network Design and Configuration Optimization with Genetic Algorithm
title_sort district heating network design and configuration optimization with genetic algorithm
publisher SDEWES Centre
series Journal of Sustainable Development of Energy, Water and Environment Systems
issn 1848-9257
publishDate 2013-12-01
description In this paper, the configuration of a district heating network which connects from the heating plant to the end users is optimized. Each end user in the network represents a building block. The connections between the heat generation plant and the end users are represented with mixed integer and the pipe friction and heat loss formulations are non-linear. In order to find the optimal district heating network configuration, genetic algorithm which handles the mixed integer nonlinear programming problem is chosen. The network configuration is represented with binary and integer encoding and is optimized in terms of the net present cost. The optimization results indicates that the optimal DH network configuration is determined by multiple factors such as the consumer heating load, the distance between the heating plant to the consumer, the design criteria regarding the pressure and temperature limitation, as well as the corresponding network heat loss.
topic District Heating Network
Optimization
Genetic Algorithm
url http://www.sdewes.org/jsdewes/pi2013.01.0022
work_keys_str_mv AT hongweili districtheatingnetworkdesignandconfigurationoptimizationwithgeneticalgorithm
AT svendsvendsen districtheatingnetworkdesignandconfigurationoptimizationwithgeneticalgorithm
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