Agreement Technologies for Energy Optimization at Home.

Area of Science:

• Building energy management
• Artificial intelligence in smart homes
• Human-computer interaction for comfort

Background:

• Current energy-saving systems prioritize environmental factors over user comfort.
• Lack of user-centric adaptation limits the adoption and effectiveness of smart building technologies.
• Integrating occupant preferences is crucial for well-being and system acceptance.

Purpose of the Study:

• To propose an intelligent energy-saving system that considers both environmental conditions and user comfort preferences.
• To develop a Multi-Agent System (MAS) architecture capable of adapting to inhabitant needs.
• To demonstrate the system's effectiveness in achieving energy savings while maintaining user comfort.

Main Methods:

• Development of a Multi-Agent System (MAS) architecture.
• Integration of Agreement Technologies (AT) for agent negotiation.
• Implementation of a negotiation process balancing user comfort and energy optimization.
• Case study conducted in an office building environment.

Main Results:

• The proposed system successfully integrated environmental data with user comfort preferences.
• The Multi-Agent System (MAS) effectively negotiated between competing demands.
• Average energy savings of 17.15% were achieved in the office building case study.
• Demonstrated feasibility of user-adaptive energy management systems.

Conclusions:

• The proposed MAS-based system offers a novel approach to energy saving by incorporating user comfort.
• Agreement Technologies (AT) facilitate effective negotiation for personalized energy management.
• The system presents a viable solution for optimizing energy consumption in buildings without compromising occupant well-being.