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Smart Heating and Cooling Networks
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Smart Heating and Cooling Networks

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J: Thermal Management".

Deadline for manuscript submissions: closed (27 March 2023) | Viewed by 13097

Special Issue Editors

Prof. Dr. Mirko Morini

E-Mail Website
Guest Editor
Department of Engineering and Architecture, University of Parma, I-43124 Parma, Italy
Interests: modelling; district heating networks; electrofuels
Special Issues, Collections and Topics in MDPI journals
Dr. Costanza Saletti

E-Mail Website
Guest Editor
Department of Engineering and Architecture, University of Parma, I-43124 Parma, Italy
Interests: district heating networks; multi-energy systems; smart control; sector integration; renewables; energy systems optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

For many years, heat has been the elephant in the room: it accounts for almost half of total energy consumption, but research and innovation mainly focused on electricity or transportation.

Recently, things have changed: strong efforts have been made to innovate this sector, with a particular reference to district heating networks. More than ten projects have been funded by the European Commission via the Horizon 2020 program, in order to decarbonize and digitalize heating and cooling networks and to foster their integration within a smarter energy system.

Research is still ongoing, but in many cases, solutions are in the demonstration phase. This Special Issue intends to collect the latest outcomes of research and innovation activities, but mainly to be a showcase for successfully demonstrated solutions for designing, managing and maintaining a heating and cooling network. Strong focus is given, but not limited to, smart controllers for flexibility and high renewable energy shares, network design tools for waste heat recovery, tools for modelling, demand forecasting, diagnosis, predictive maintenance or retrofitting.

This Special Issue aims to be a source for future developments, but also a knowledge base for the dissemination of best practices and the promotion of their replication.

Prof. Dr. Mirko Morini
Dr. Costanza Saletti
Guest Editors

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. Energies is an international peer-reviewed open access semimonthly 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 2600 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

  • smart energy systems
  • digitalization
  • energy efficiency
  • district heating and cooling networks
  • renewable energy

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Published Papers (5 papers)

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Research

20 pages, 5996 KiB  
Article
Maximizing Energy Performance of University Campus Buildings through BIM Software and Multicriteria Optimization Methods
by Angeliki Tsantili, Irene Koronaki and Vasilis Polydoros
Energies 2023, 16(5), 2291; https://doi.org/10.3390/en16052291 - 27 Feb 2023
Cited by 5 | Viewed by 2431
Abstract
University buildings have high energy requirements due to their size, numerous users, and activities, which considerably contribute to environmental contamination. Implementing energy-saving solutions in these structures has a favorable influence on the economics and the conservation of energy resources. A higher education building’s [...] Read more.
University buildings have high energy requirements due to their size, numerous users, and activities, which considerably contribute to environmental contamination. Implementing energy-saving solutions in these structures has a favorable influence on the economics and the conservation of energy resources. A higher education building’s energy behavior can be simulated using software to identify the optimal strategies that result in energy savings. In this research, Autodesk Revit, Autodesk Insight, and Green Building Studio are among the programs utilized to examine the energy efficiency of the university building in four European cities. Following the development of several energy-saving scenarios for the building, the offered solutions are evaluated based on their annual energy consumption, energy costs, and CO2  emissions. Finally, multicriteria analysis techniques such as the AHP and PROMETHEE are applied to choose the best scenario for each instance. The study’s findings indicate that the ASHRAE Terminal Package Heat Pump scenario performed well in all of the cities examined, reducing yearly energy usage by 43.75% in Wien and annual energy costs by 47.31% in Mallorca. In comparison, the scenario utilizing a high-efficiency VAV system with a gas boiler and chiller came in last in all situations, resulting in a decrease of 12.67% in Mallorca’s annual energy usage and a reduction of 17.57% in Palermo’s annual energy expenses. Full article
(This article belongs to the Special Issue Smart Heating and Cooling Networks)
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20 pages, 5515 KiB  
Article
Optimized Operation and Sizing of Solar District Heating Networks with Small Daily Storage
by Régis Delubac, Mohammad Sadr, Sabine Sochard, Sylvain Serra and Jean-Michel Reneaume
Energies 2023, 16(3), 1335; https://doi.org/10.3390/en16031335 - 27 Jan 2023
Cited by 5 | Viewed by 1833
Abstract
To continue improving the integration of solar thermal in district heating networks, optimization tools that can study both sizing and operation of heating plants are needed. In this article, the ISORC tool was used to study the sizing and coupled operation of smaller [...] Read more.
To continue improving the integration of solar thermal in district heating networks, optimization tools that can study both sizing and operation of heating plants are needed. In this article, the ISORC tool was used to study the sizing and coupled operation of smaller storage and solar fields with other heating sources such as biomass and gas boilers. For this, a k-medoids algorithm was applied to select consecutive characteristic days to size the system based on an optimal operation of consecutive days in the same season. The formulated problem was nonlinear, and the objective function to be minimized was the total cost. Two case studies with different day constructions and distributions were studied with various sensitivity analysis. The formulation and methodology allowed us to study different cases and situations easily and proved the importance of the selection and attribution of typical days. In all cases, the results showed that even with a daily approach, solar thermal covers approximately 20% of the demand, which demonstrates the relevance of considering and developing small daily storage with small solar fields. Full article
(This article belongs to the Special Issue Smart Heating and Cooling Networks)
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18 pages, 3039 KiB  
Article
Sector Coupling Potential of a District Heating Network by Consideration of Residual Load and CO2 Emissions
by Melanie Werner, Sebastian Muschik, Mathias Ehrenwirth, Christoph Trinkl and Tobias Schrag
Energies 2022, 15(17), 6281; https://doi.org/10.3390/en15176281 - 28 Aug 2022
Cited by 2 | Viewed by 1493
Abstract
The growing share of fluctuating renewable electricity production within the German energy system causes the increasing necessity for flexible consumers, producers, and storage technologies to balance supply and demand. District heating networks with combined heat and power units, Power-to-Heat applications, and thermal energy [...] Read more.
The growing share of fluctuating renewable electricity production within the German energy system causes the increasing necessity for flexible consumers, producers, and storage technologies to balance supply and demand. District heating networks with combined heat and power units, Power-to-Heat applications, and thermal energy storage capacities can serve as one of these flexible options. In this context, a simulation model of the district heating network of the rural community Dollnstein, Germany, was built. With the residual load of different regional areas (Germany, Bavaria, Eichstätt, Dollnstein) it is investigated, how the heat generators can operate in an electricity market beneficial way. Two different control algorithms were evaluated: Due to a correlation between the residual loads and the CO2 emissions of the electricity mix, the CO2 savings achieved by this control algorithm are determined. Another way to operate electricity market beneficial is to consider the current CO2 emissions of each region. The main outcomes of this paper are, that there is a high potential for sector coupling by shifting the operation times of a CHP and a heat pump according to the residual load. The electricity demand of the heat pump can be met in terms of low CO2 emissions of the electricity mix, while the CHP can replace electricity with high CO2 emissions. These results can be improved, by considering not the residual load but the current CO2 emissions in the control algorithm. Full article
(This article belongs to the Special Issue Smart Heating and Cooling Networks)
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Graphical abstract

21 pages, 837 KiB  
Article
A Shallow Neural Network Approach for the Short-Term Forecast of Hourly Energy Consumption
by Andrea Manno, Emanuele Martelli and Edoardo Amaldi
Energies 2022, 15(3), 958; https://doi.org/10.3390/en15030958 - 28 Jan 2022
Cited by 17 | Viewed by 2553
Abstract
The forecasts of electricity and heating demands are key inputs for the efficient design and operation of energy systems serving urban districts, buildings, and households. Their accuracy may have a considerable effect on the selection of the optimization approach and on the solution [...] Read more.
The forecasts of electricity and heating demands are key inputs for the efficient design and operation of energy systems serving urban districts, buildings, and households. Their accuracy may have a considerable effect on the selection of the optimization approach and on the solution quality. In this work, we describe a supervised learning approach based on shallow Artificial Neural Networks to develop an accurate model for predicting the daily hourly energy consumption of an energy district 24 h ahead. Predictive models are generated for each one of the two considered energy types, namely electricity and heating. Single-layer feedforward neural networks are trained with the efficient and robust decomposition algorithm DEC proposed by Grippo et al. on a data set of historical data, including, among others, carefully selected information related to the hourly energy consumption of the energy district and the hourly weather data of the region where the district is located. Three different case studies are analyzed: a medium-size hospital located in the Emilia-Romagna Italian region, the whole Politecnico di Milano University campus, and a single building of a department belonging to the latter. The computational results indicate that the proposed method with enriched data inputs compares favorably with the benchmark forecasting and Machine Learning techniques, namely, ARIMA, Support Vector Regression and long short-term memory networks. Full article
(This article belongs to the Special Issue Smart Heating and Cooling Networks)
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20 pages, 6089 KiB  
Article
Efficient District Heating in a Decarbonisation Perspective: A Case Study in Italy
by Mattia Ricci, Paolo Sdringola, Salvatore Tamburrino, Giovanni Puglisi, Elena Di Donato, Maria Alessandra Ancona and Francesco Melino
Energies 2022, 15(3), 948; https://doi.org/10.3390/en15030948 - 27 Jan 2022
Cited by 14 | Viewed by 3713
Abstract
The European and national regulations in the decarbonisation path towards 2050 promote district heating in achieving the goals of efficiency, energy sustainability, use of renewables, and reduction of fossil fuel use. Improved management and optimisation, use of RES, and waste heat/cold sources decrease [...] Read more.
The European and national regulations in the decarbonisation path towards 2050 promote district heating in achieving the goals of efficiency, energy sustainability, use of renewables, and reduction of fossil fuel use. Improved management and optimisation, use of RES, and waste heat/cold sources decrease the overall demand for primary energy, a condition that is further supported by building renovations and new construction of under (almost) zero energy buildings, with a foreseeable decrease in the temperature of domestic heating systems. Models for the simulation of efficient thermal networks were implemented and described in this paper, together with results from a real case study in Italy, i.e., University Campus of Parma. Activities include the creation and validation of calculation codes and specific models in the Modelica language (Dymola software), aimed at investigating stationary regimes and dynamic behaviour as well. An indirect heat exchange substation was coupled with a resistive-capacitive model, which describes the building behaviour and the thermal exchanges by the use of thermos-physical parameters. To optimise indoor comfort conditions and minimise consumption, dynamic simulations were carried out for different operating sets: modulating the supply temperature in the plant depending on external conditions (Scenario 4) decreases the supplied thermal energy (−2.34%) and heat losses (−8.91%), even if a lower temperature level results in higher electricity consumption for pumping (+12.96%), the total energy consumption is reduced by 1.41%. A simulation of the entire heating season was performed for the optimised scenario, combining benefits from turning off the supply in the case of no thermal demand (Scenario 3) and from the modulation of the supply temperature (Scenario 4), resulting in lower energy consumption (the thermal energy supplied by the power plant −3.54%, pumping +7.76%), operating costs (−2.40), and emissions (−3.02%). The energy balance ex-ante and ex-post deep renovation in a single user was then assessed, showing how lowering the network operating temperature at 55 °C decreases the supplied thermal energy (−22.38%) and heat losses (−22.11%) with a slightly higher pumping consumption (+3.28%), while maintaining good comfort conditions. These promising results are useful for evaluating the application of low-temperature operations to the existing district heating networks, especially for large interventions of building renovation, and confirm their potential contribution to the energy efficiency targets. Full article
(This article belongs to the Special Issue Smart Heating and Cooling Networks)
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