Towards sustainable energy-efficient communities based on a scheduling algorithm
Authors
Bravo Muñoz, IgnacioIdentifiers
Permanent link (URI): http://hdl.handle.net/10017/46997DOI: 10.3390/s19183973
ISSN: 7803-7842
Publisher
MDPI
Date
2019-09-14Funders
Comunidad de Madrid
Bibliographic citation
Cruz, C., Palomar, E., Bravo, I. & Gardel, A. 2019, "Towards sustainable energy-efficient communities based on a scheduling algorithm", Sensors, 2019, v. 19, n. 18, 3973.
Keywords
Cooperative smart community
Scheduling algorithm
Consumer preferences
Renewables
Project
2017-T1/TIC-5184 (Comunidad de Madrid)
Document type
info:eu-repo/semantics/article
Version
info:eu-repo/semantics/publishedVersion
Publisher's version
https://doi.org/10.3390/s19183973Rights
Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Access rights
info:eu-repo/semantics/openAccess
Abstract
The Internet of Things (IoT) and Demand Response (DR) combined have transformed the way Information and Communication Technologies (ICT) contribute to saving energy and reducing costs, while also giving consumers more control over their energy footprint. Unlike current price and incentive based DR strategies, we propose a DR model that promotes consumers reaching coordinated behaviour towards more sustainable (and green) communities. A cooperative DR system is designed not only to bolster energy efficiency management at both home and district levels, but also to integrate the renewable energy resource information into the community's energy management. Initially conceived in a centralised way, a data collector called the "aggregator" will handle the operation scheduling requirements given the consumers' time preferences and the available electricity supply from renewables. Evaluation on the algorithm implementation shows feasible computational cost (CC) in different scenarios of households, communities and consumer behaviour. Number of appliances and timeframe flexibility have the greatest impact on the reallocation cost. A discussion on the communication, security and hardware platforms is included prior to future pilot deployment.
Files in this item
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Towards_Cruz_Sensors_2019.pdf | 961.6Kb |
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Files | Size | Format |
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Towards_Cruz_Sensors_2019.pdf | 961.6Kb |
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