District Heating and Cooling Networks
Conventional thermal power generating plants reject a large amount of energy every year. If this rejected heat were to be used through district heating networks, given prior energy valorisation, there would be a noticeable decrease in the amount of fossil fuels imported for heating. As a consequence...
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| Fformat: | Online |
| Iaith: | Saesneg |
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MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Pynciau: | |
| Mynediad Ar-lein: | 46070 |
| Tagiau: |
Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!
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| _version_ | 1869520099265740800 |
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| author | Borge Diez, David Colmenar Santos, Antonio Rosales Asensio, Enrique |
| author_browse | Borge Diez, David Colmenar Santos, Antonio Rosales Asensio, Enrique |
| author_facet | Borge Diez, David Colmenar Santos, Antonio Rosales Asensio, Enrique |
| author_sort | Borge Diez, David |
| collection | Directory of Open Access Books |
| description | Conventional thermal power generating plants reject a large amount of energy every year. If this rejected heat were to be used through district heating networks, given prior energy valorisation, there would be a noticeable decrease in the amount of fossil fuels imported for heating. As a consequence, benefits would be experienced in the form of an increase in energy efficiency, an improvement in energy security, and a minimisation of emitted greenhouse gases. Given that heat demand is not expected to decrease significantly in the medium term, district heating networks show the greatest potential for the development of cogeneration. Due to their cost competitiveness, flexibility in terms of the ability to use renewable energy resources (such as geothermal or solar thermal) and fossil fuels (more specifically the residual heat from combustion), and the fact that, in some cases, losses to a country/region’s energy balance can be easily integrated into district heating networks (which would not be the case in a “fully electric” future), district heating (and cooling) networks and cogeneration could become a key element for a future with greater energy security, while being more sustainable, if appropriate measures were implemented. This book therefore seeks to propose an energy strategy for a number of cities/regions/countries by proposing appropriate measures supported by detailed case studies. |
| format | Online |
| id | doab-20.500.12854ir-45291 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-452912024-04-11T15:10:13Z District Heating and Cooling Networks Borge Diez, David Colmenar Santos, Antonio Rosales Asensio, Enrique TA1-2040 T1-995 district heating 4th generation district heating data mining algorithms energy system modeling neural networks baseline model hydronic pavement system biomass district heating for rural locations CO2 emissions abatement low temperature networks ultralow-temperature district heating domestic optimization energy efficiency sustainable energy big data frameworks verification energy prediction parameter analysis greenhouse gas emissions time delay heat pumps primary energy use retrofit energy consumption forecast district heating (DH) network low-temperature district heating thermal inertia variable-temperature district heating data streams analysis Computational Fluid Dynamics energy management in renovated building Scotland heat reuse thermally activated cooling district cooling space cooling Gulf Cooperation Council biomass TRNSYS hot climate optimal control air-conditioning machine learning low temperature district heating system data center twin-pipe residential prediction algorithm CFD model nZEB thermal-hydraulic performance thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Conventional thermal power generating plants reject a large amount of energy every year. If this rejected heat were to be used through district heating networks, given prior energy valorisation, there would be a noticeable decrease in the amount of fossil fuels imported for heating. As a consequence, benefits would be experienced in the form of an increase in energy efficiency, an improvement in energy security, and a minimisation of emitted greenhouse gases. Given that heat demand is not expected to decrease significantly in the medium term, district heating networks show the greatest potential for the development of cogeneration. Due to their cost competitiveness, flexibility in terms of the ability to use renewable energy resources (such as geothermal or solar thermal) and fossil fuels (more specifically the residual heat from combustion), and the fact that, in some cases, losses to a country/region’s energy balance can be easily integrated into district heating networks (which would not be the case in a “fully electric” future), district heating (and cooling) networks and cogeneration could become a key element for a future with greater energy security, while being more sustainable, if appropriate measures were implemented. This book therefore seeks to propose an energy strategy for a number of cities/regions/countries by proposing appropriate measures supported by detailed case studies. 2021-02-11T11:36:25Z 2021-02-11T11:36:25Z 2020-06-09 16:38:57 2020 book 46070 9783039288403 9783039288397 https://directory.doabooks.org/handle/20.500.12854/45291 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/2263 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03928-840-3 10.3390/books978-3-03928-840-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039288403 9783039288397 270 open access |
| spellingShingle | TA1-2040 T1-995 district heating 4th generation district heating data mining algorithms energy system modeling neural networks baseline model hydronic pavement system biomass district heating for rural locations CO2 emissions abatement low temperature networks ultralow-temperature district heating domestic optimization energy efficiency sustainable energy big data frameworks verification energy prediction parameter analysis greenhouse gas emissions time delay heat pumps primary energy use retrofit energy consumption forecast district heating (DH) network low-temperature district heating thermal inertia variable-temperature district heating data streams analysis Computational Fluid Dynamics energy management in renovated building Scotland heat reuse thermally activated cooling district cooling space cooling Gulf Cooperation Council biomass TRNSYS hot climate optimal control air-conditioning machine learning low temperature district heating system data center twin-pipe residential prediction algorithm CFD model nZEB thermal-hydraulic performance thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Borge Diez, David Colmenar Santos, Antonio Rosales Asensio, Enrique District Heating and Cooling Networks |
| title | District Heating and Cooling Networks |
| title_full | District Heating and Cooling Networks |
| title_fullStr | District Heating and Cooling Networks |
| title_full_unstemmed | District Heating and Cooling Networks |
| title_short | District Heating and Cooling Networks |
| title_sort | district heating and cooling networks |
| topic | TA1-2040 T1-995 district heating 4th generation district heating data mining algorithms energy system modeling neural networks baseline model hydronic pavement system biomass district heating for rural locations CO2 emissions abatement low temperature networks ultralow-temperature district heating domestic optimization energy efficiency sustainable energy big data frameworks verification energy prediction parameter analysis greenhouse gas emissions time delay heat pumps primary energy use retrofit energy consumption forecast district heating (DH) network low-temperature district heating thermal inertia variable-temperature district heating data streams analysis Computational Fluid Dynamics energy management in renovated building Scotland heat reuse thermally activated cooling district cooling space cooling Gulf Cooperation Council biomass TRNSYS hot climate optimal control air-conditioning machine learning low temperature district heating system data center twin-pipe residential prediction algorithm CFD model nZEB thermal-hydraulic performance thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | TA1-2040 T1-995 district heating 4th generation district heating data mining algorithms energy system modeling neural networks baseline model hydronic pavement system biomass district heating for rural locations CO2 emissions abatement low temperature networks ultralow-temperature district heating domestic optimization energy efficiency sustainable energy big data frameworks verification energy prediction parameter analysis greenhouse gas emissions time delay heat pumps primary energy use retrofit energy consumption forecast district heating (DH) network low-temperature district heating thermal inertia variable-temperature district heating data streams analysis Computational Fluid Dynamics energy management in renovated building Scotland heat reuse thermally activated cooling district cooling space cooling Gulf Cooperation Council biomass TRNSYS hot climate optimal control air-conditioning machine learning low temperature district heating system data center twin-pipe residential prediction algorithm CFD model nZEB thermal-hydraulic performance thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | 46070 |
| work_keys_str_mv | AT borgediezdavid districtheatingandcoolingnetworks AT colmenarsantosantonio districtheatingandcoolingnetworks AT rosalesasensioenrique districtheatingandcoolingnetworks |