Demand-Response in Smart Buildings
This book represents the Special Issue of Energies, entitled “Demand-Response in Smart Buildings”, that was published in the section “Energy and Buildings”. This Special Issue is a collection of original scientific contributions and review papers that deal with smart buildings and communities. Dema...
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| Format: | Online |
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| Jezik: | engleski |
| Izdano: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Teme: | |
| Online pristup: | ONIX_20210501_9783039282661_766 |
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| _version_ | 1869528419496099840 |
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| collection | Directory of Open Access Books |
| description | This book represents the Special Issue of Energies, entitled “Demand-Response in Smart Buildings”, that was published in the section “Energy and Buildings”. This Special Issue is a collection of original scientific contributions and review papers that deal with smart buildings and communities. Demand response (DR) offers the capability to apply changes in the energy usage of consumers—from their normal consumption patterns—in response to changes in energy pricing over time. This leads to a lower energy demand during peak hours or during periods when an electricity grid’s reliability is put at risk. Therefore, demand response is a reduction in demand designed to reduce peak load or avoid system emergencies. Hence, demand response can be more cost-effective than adding generation capabilities to meet the peak and/or occasional demand spikes. The underlying objective of DR is to actively engage customers in modifying their consumption in response to pricing signals. Demand response is expected to increase energy market efficiency and the security of supply, which will ultimately benefit customers by way of options for managing their electricity costs leading to reduced environmental impact. |
| format | Online |
| id | doab-20.500.12854ir-69020 |
| 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-690202024-04-11T15:10:33Z Demand-Response in Smart Buildings Kolokotsa, Denia Pignatta, Gloria Gobakis, Kostas demand response artificial neural network power predictions energy management genetic algorithm optimisation microgrid smart grid requests time cloud computing response time processing time resource allocation fog computing energy resource energy security energy sources Slovakia energy flexibility retrofitting interventions residential consumption electrification in the built environment smart cities smart energy management India energy efficiency low-carbon mobility water-energy nexus thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology This book represents the Special Issue of Energies, entitled “Demand-Response in Smart Buildings”, that was published in the section “Energy and Buildings”. This Special Issue is a collection of original scientific contributions and review papers that deal with smart buildings and communities. Demand response (DR) offers the capability to apply changes in the energy usage of consumers—from their normal consumption patterns—in response to changes in energy pricing over time. This leads to a lower energy demand during peak hours or during periods when an electricity grid’s reliability is put at risk. Therefore, demand response is a reduction in demand designed to reduce peak load or avoid system emergencies. Hence, demand response can be more cost-effective than adding generation capabilities to meet the peak and/or occasional demand spikes. The underlying objective of DR is to actively engage customers in modifying their consumption in response to pricing signals. Demand response is expected to increase energy market efficiency and the security of supply, which will ultimately benefit customers by way of options for managing their electricity costs leading to reduced environmental impact. 2021-05-01T15:35:33Z 2021-05-01T15:35:33Z 2020 book ONIX_20210501_9783039282661_766 9783039282661 9783039282678 https://directory.doabooks.org/handle/20.500.12854/69020 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/2789 https://mdpi.com/books/pdfview/book/2789 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03928-267-8 10.3390/books978-3-03928-267-8 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039282661 9783039282678 112 Basel, Switzerland open access |
| spellingShingle | demand response artificial neural network power predictions energy management genetic algorithm optimisation microgrid smart grid requests time cloud computing response time processing time resource allocation fog computing energy resource energy security energy sources Slovakia energy flexibility retrofitting interventions residential consumption electrification in the built environment smart cities smart energy management India energy efficiency low-carbon mobility water-energy nexus thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Demand-Response in Smart Buildings |
| title | Demand-Response in Smart Buildings |
| title_full | Demand-Response in Smart Buildings |
| title_fullStr | Demand-Response in Smart Buildings |
| title_full_unstemmed | Demand-Response in Smart Buildings |
| title_short | Demand-Response in Smart Buildings |
| title_sort | demand response in smart buildings |
| topic | demand response artificial neural network power predictions energy management genetic algorithm optimisation microgrid smart grid requests time cloud computing response time processing time resource allocation fog computing energy resource energy security energy sources Slovakia energy flexibility retrofitting interventions residential consumption electrification in the built environment smart cities smart energy management India energy efficiency low-carbon mobility water-energy nexus thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | demand response artificial neural network power predictions energy management genetic algorithm optimisation microgrid smart grid requests time cloud computing response time processing time resource allocation fog computing energy resource energy security energy sources Slovakia energy flexibility retrofitting interventions residential consumption electrification in the built environment smart cities smart energy management India energy efficiency low-carbon mobility water-energy nexus thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20210501_9783039282661_766 |