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Planning, Simulation, Optimization and Operation of District Heating and Cooling...
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Planning, Simulation, Optimization and Operation of District Heating and Cooling Systems

A special issue of Resources (ISSN 2079-9276).

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 11042

Special Issue Editor

Dr. Ingo Leusbrock

E-Mail Website
Guest Editor
AEE—Institute for Sustainable Technologies, Gleisdorf, Austria
Interests: sustainable energy systems; district heating and cooling; modeling and simulation of energy systems; (GIS-based) planning tools and concepts; urban resource cycles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Our current energy demand stems approximately 50% from our demand for heating and cooling. The achievement of mid- and long-term international and national climate goals is consequently only possible if we find sustainable solutions for this demand. District heating and cooling (DHC) systems are considered highly suitable solutions to address this challenge, as these systems allow us to a) integrate renewable heat sources and thermal storages and b) provide flexible and cost-effective services through application of, e.g., advanced data analysis, demand side management and other systemic interventions. Nevertheless, growing scale, integration of more technical components and increased interaction between them in combination with systen-wide approaches such as advanced monitoring and control schemes lead to an increase in complexity during planning, design, and later operation. Thus, sophicticated and refined tools and methods are necessary for, e.g., simulation and optimization during conceptualization, implementation, and operation, as well as system-wide and holistic approaches during all steps, not only on technical aspects, but also on transdisciplinary aspects.

In this Special Issue, we invite papers that provide new insights and experiences as well as highlight new possibilities in planning, simulation, optimization, and actual operation of sustainable and cost-effective DHC systems. We look forward receiving papers that address one or more of the following issues:

  • (Spatial) planning methods and approaches (including non-technical aspects) for district heating and cooling concept development, extension, and transformation to 100% renewable-based systems;
  • New perspectives on modeling, simulation, and (techno-economic) optimization of DHC systems and its technical components;
  • DHC systems as an energy hub and part of a smart sector integration;
  • Development of novel monitoring and control methods for DHC systems and application of advanced data analysis methods.

Dr. Ingo Leusbrock
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Resources is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • district heating
  • district cooling
  • sustainable energy
  • modelling, simulation and optimization
  • monitoring and control
  • (spatial) planning
  • data analysis

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Published Papers (3 papers)

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Research

17 pages, 3415 KiB  
Article
Enhancement of a District Heating Substation as Part of a Low-Investment Optimization Strategy for District Heating Systems
by Anna Vannahme, Mathias Ehrenwirth and Tobias Schrag
Resources 2021, 10(5), 53; https://doi.org/10.3390/resources10050053 - 19 May 2021
Cited by 3 | Viewed by 2899
Abstract
In an ongoing project, low-investment measures for the optimization of district heating systems are analyzed. The optimization strategies are collected in a catalog, which is the core of a guideline. The application of this guideline is demonstrated using two concrete district heating networks [...] Read more.
In an ongoing project, low-investment measures for the optimization of district heating systems are analyzed. The optimization strategies are collected in a catalog, which is the core of a guideline. The application of this guideline is demonstrated using two concrete district heating networks as examples. In this study, the improvement of an analog controlled district heating substation by an electronic controller is investigated. High supply temperatures and heat losses are often a challenge in district heating networks. The district heating substations have a major influence on the network return temperatures. The comparison of the two substation setups with analog and electronic controllers is carried out by laboratory measurement. It can be shown that the return temperatures can be reduced by an average of 20 K in winter and transition, as well as 16 K in summer. The district heating network losses are calculated for one of both specific district heating networks. They are calculated from the ratio of network losses to generated energy. The generated energy is the sum of network losses and consumer demand. The thermal losses of the network can be reduced by 3%. The volume flow in the heating network can be reduced to a quarter. Therefore, the pumping energy requirement drops sharply since these changes cubically affect the volume flow. Full article
(This article belongs to the Special Issue Planning, Simulation, Optimization and Operation of District Heating and Cooling Systems)
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19 pages, 4280 KiB  
Article
A Method for Optimizing and Spatially Distributing Heating Systems by Coupling an Urban Energy Simulation Platform and an Energy System Model
by Annette Steingrube, Keyu Bao, Stefan Wieland, Andrés Lalama, Pithon M. Kabiro, Volker Coors and Bastian Schröter
Resources 2021, 10(5), 52; https://doi.org/10.3390/resources10050052 - 18 May 2021
Cited by 7 | Viewed by 3063
Abstract
District heating is seen as an important concept to decarbonize heating systems and meet climate mitigation goals. However, the decision related to where central heating is most viable is dependent on many different aspects, like heating densities or current heating structures. An urban [...] Read more.
District heating is seen as an important concept to decarbonize heating systems and meet climate mitigation goals. However, the decision related to where central heating is most viable is dependent on many different aspects, like heating densities or current heating structures. An urban energy simulation platform based on 3D building objects can improve the accuracy of energy demand calculation on building level, but lacks a system perspective. Energy system models help to find economically optimal solutions for entire energy systems, including the optimal amount of centrally supplied heat, but do not usually provide information on building level. Coupling both methods through a novel heating grid disaggregation algorithm, we propose a framework that does three things simultaneously: optimize energy systems that can comprise all demand sectors as well as sector coupling, assess the role of centralized heating in such optimized energy systems, and determine the layouts of supplying district heating grids with a spatial resolution on the street level. The algorithm is tested on two case studies; one, an urban city quarter, and the other, a rural town. In the urban city quarter, district heating is economically feasible in all scenarios. Using heat pumps in addition to CHPs increases the optimal amount of centrally supplied heat. In the rural quarter, central heat pumps guarantee the feasibility of district heating, while standalone CHPs are more expensive than decentral heating technologies. Full article
(This article belongs to the Special Issue Planning, Simulation, Optimization and Operation of District Heating and Cooling Systems)
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20 pages, 721 KiB  
Article
Experiences from City-Scale Simulation of Thermal Grids
by Johan Simonsson, Khalid Tourkey Atta, Gerald Schweiger and Wolfgang Birk
Resources 2021, 10(2), 10; https://doi.org/10.3390/resources10020010 - 25 Jan 2021
Cited by 13 | Viewed by 4085
Abstract
Dynamic simulation of district heating and cooling networks has an increased importance in the transition towards renewable energy sources and lower temperature district heating grids, as both temporal and spatial behavior need to be considered. Even though much research and development has been [...] Read more.
Dynamic simulation of district heating and cooling networks has an increased importance in the transition towards renewable energy sources and lower temperature district heating grids, as both temporal and spatial behavior need to be considered. Even though much research and development has been performed in the field, there are several pitfalls and challenges towards dynamic district heating and cooling simulation for everyday use. This article presents the experiences from developing and working with a city-scale simulator of a district heating grid located in Luleå, Sweden. The grid model in the case study is a physics based white-box model, while consumer models are either data-driven black-box or gray-box models. The control system and operator models replicate the manual and automatic operation of the combined heat and power plant. Using the functional mock-up interface standard, a co-simulation environment integrates all the models. Further, the validation of the simulator is discussed. Lessons learned from the project are presented along with future research directions, corresponding to identified gaps and challenges. Full article
(This article belongs to the Special Issue Planning, Simulation, Optimization and Operation of District Heating and Cooling Systems)
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