Towards Intelligent District Heating

Document type: Licentiates
Full text:
Author(s): Christian Johansson
Title: Towards Intelligent District Heating
Series: Blekinge Institute of Technology Licentiate Dissertion Series
Year: 2010
Issue: 6
ISBN: 978-91-7295-181-5
ISSN: 1650-2140
Publisher: Blekinge Institute of Technology
City: Karlskrona
Organization: Blekinge Institute of Technology
Department: School of Computing (Sektionen för datavetenskap och kommunikation)
School of Computing S-371 79 Karlskrona
+46 455 38 50 00
http://www.bth.se/com
Authors e-mail: chj@bth.se
Language: English
Abstract: A district heating system consists of one or more production units supplying energy in the form of heated water through a distribution pipe network to a multitude of consumers. District heating systems come in a range of different forms and sizes; from small independent systems within industrial estates or university campuses to large city-wide systems supplying millions of consumers with heating and hot water. The geographically dispersed layout of district heating systems suggest that they are suitable for distributed optimization and management. However, this would imply a transition from the classical production-centric perspective normally found within district heating management to a more consumer-centric perspective. In this work we use multi-agent based systems in order to implement distributed policies for operational planning within district heating systems. We also develop models for simulating the dynamics of district heating systems in order to evaluate those policies and their use in computer-based demand side management approaches for improving operational planning and resource management. These policies are then implemented in real world industrial settings and their performance, as well as implementation issues, are analysed and evaluated. It is shown that distributed policies can lead to significant benefits compared to current schemes with respect to energy usage and heat load management at an operational level.
Subject: Computer Science\Artificial Intelligence
Computer Science\Distributed Computing
URN: urn:nbn:se:bth-00467
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