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

Carlos Cruz1, Esther Palomar2, Ignacio Bravo3

  • 1Department of Electronics, University of Alcala, Alcala de Henares, 28871 Madrid, Spain. carlos.cruzt@uah.es.

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Summary
This summary is machine-generated.

This study introduces a cooperative Demand Response (DR) model using the Internet of Things (IoT) for coordinated energy management. It integrates renewable energy, enhancing efficiency and promoting sustainable communities.

Keywords:
consumer preferencescooperative smart communityrenewablesscheduling algorithm

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Area of Science:

  • Energy Systems Engineering
  • Computer Science
  • Environmental Science

Background:

  • The integration of Information and Communication Technologies (ICT) with the Internet of Things (IoT) and Demand Response (DR) offers significant potential for energy savings and cost reduction.
  • Current DR strategies primarily rely on price and incentives, often lacking mechanisms for coordinated consumer behavior towards sustainability.

Purpose of the Study:

  • To propose a novel cooperative Demand Response (DR) model that fosters coordinated consumer behavior for sustainable communities.
  • To enhance energy efficiency at both household and district levels by integrating renewable energy resource information.

Main Methods:

  • A centralized cooperative DR system design featuring an 'aggregator' data collector.
  • The aggregator manages operation scheduling based on consumer time preferences and available renewable energy supply.

Main Results:

  • Algorithm evaluation demonstrates feasible computational cost (CC) across various scenarios (households, communities, consumer behaviors).
  • The number of appliances and timeframe flexibility were identified as key factors influencing reallocation cost.

Conclusions:

  • The proposed cooperative DR model effectively integrates renewable energy and promotes coordinated consumer behavior for energy efficiency.
  • The system shows promise for pilot deployment, with further discussion on communication, security, and hardware platforms.