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Open AccessArticle

Towards Sustainable Energy-Efficient Communities Based on a Scheduling Algorithm

Department of Electronics, University of Alcala, Alcala de Henares, 28871 Madrid, Spain
Author to whom correspondence should be addressed.
Sensors 2019, 19(18), 3973;
Received: 11 August 2019 / Revised: 3 September 2019 / Accepted: 10 September 2019 / Published: 14 September 2019
(This article belongs to the Special Issue Green, Energy-Efficient and Sustainable Networks)
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. View Full-Text
Keywords: cooperative smart community; scheduling algorithm; consumer preferences; renewables cooperative smart community; scheduling algorithm; consumer preferences; renewables
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Cruz, C.; Palomar, E.; Bravo, I.; Gardel, A. Towards Sustainable Energy-Efficient Communities Based on a Scheduling Algorithm. Sensors 2019, 19, 3973.

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