Towards Sustainable Energy-Efficient Communities Based on a Scheduling Algorithm.

Sensors (Basel)

Department of Electronics, University of Alcala, Alcala de Henares, 28871 Madrid, Spain.

Published: September 2019

AI Article Synopsis

  • The combination of the Internet of Things (IoT) and Demand Response (DR) is revolutionizing how Information and Communication Technologies (ICT) improve energy savings and reduce costs while empowering consumers to manage their energy use.
  • A new DR model encourages coordinated consumer behavior for creating more sustainable communities, compared to traditional incentive-based approaches.
  • The proposed system uses a centralized "aggregator" to manage energy supply from renewables and considers various factors like appliance numbers and flexibility in scheduling, with evaluations indicating promising computational costs for diverse consumer scenarios.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767685PMC
http://dx.doi.org/10.3390/s19183973DOI Listing

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