Amidst growing environmental concerns and the push for sustainability, the intricacies of energy management in diverse building settings demand innovative solutions. Traditional strategies fail to address the unique characteristics and needs of different building types and users leading to inefficiencies and a lack of optimization in energy use. This study presents a sophisticated building energy management system, assessed via pilot implementations, which utilizes a platform based on adaptive and intelligent edge computing. This comprehensive system integrates various elements such as smart meters, HVAC controls, electric vehicle charging stations, and smart plugs. Utilizing the ICT PSP framework, the methodology encompasses rigorous data collection and analysis, emphasizing usability, error rectification, and the detailed monitoring of impacts. Key findings reveal that tailored energy management solutions, augmented by real-time data and user-centric interfaces, significantly improve energy efficiency. The study also highlighted the impact of socio-economic factors and weather conditions on energy consumption, underscoring the necessity of incorporating these variables into energy management strategies. The integration of demand-side management (DSM) through energy retailers, distribution system operators (DSO), or other power grid stakeholders has yielded valuable insights into external factors affecting energy consumption patterns. Specifically, these insights pertain to electricity tariffs and consumer behavior.

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Optimizing Building Energy Management Leveraging Adaptive Edge Computing for Enhanced Efficiency and Occupant Well-Being

  • Sergio Márquez-Sánchez,
  • Sergio Alonso-Rollán,
  • Hayla Nahom,
  • Aiman Erbad,
  • Javier Hernandez Fernandez

摘要

Amidst growing environmental concerns and the push for sustainability, the intricacies of energy management in diverse building settings demand innovative solutions. Traditional strategies fail to address the unique characteristics and needs of different building types and users leading to inefficiencies and a lack of optimization in energy use. This study presents a sophisticated building energy management system, assessed via pilot implementations, which utilizes a platform based on adaptive and intelligent edge computing. This comprehensive system integrates various elements such as smart meters, HVAC controls, electric vehicle charging stations, and smart plugs. Utilizing the ICT PSP framework, the methodology encompasses rigorous data collection and analysis, emphasizing usability, error rectification, and the detailed monitoring of impacts. Key findings reveal that tailored energy management solutions, augmented by real-time data and user-centric interfaces, significantly improve energy efficiency. The study also highlighted the impact of socio-economic factors and weather conditions on energy consumption, underscoring the necessity of incorporating these variables into energy management strategies. The integration of demand-side management (DSM) through energy retailers, distribution system operators (DSO), or other power grid stakeholders has yielded valuable insights into external factors affecting energy consumption patterns. Specifically, these insights pertain to electricity tariffs and consumer behavior.