Dedalus Discoveries | Revolutionising building energy management: AI-driven demand response for a sustainable future

Engineering, CARTIF, and Università Politecnica delle Marche, as scientific partners in the Dedalus project, have published a new paper titled “Methodological approach for optimizing demand response in building energy management through AI-enhanced comfort-based flexibility models.”
The paper introduces a novel methodology that leverages artificial intelligence to optimize demand response  in building energy management systems, aligning energy consumption dynamically with efficiency objectives.

By analyzing historical data and real-time inputs, AI algorithms forecast energy needs and optimize the performance of critical building systems such as heating, ventilation, air conditioning, and lighting, striking a balance between energy efficiency and operational demands. This methodology is being tested across several pilot projects under the DEDALUS initiative, demonstrating its adaptability to various environments and its capacity to enhance DR strategies.

The AI-driven approach provides significant demand-side flexibility for energy markets, promoting a more sustainable built environment by reducing carbon footprints and optimizing resource use in line with market requirements. The findings underscore AI’s transformative potential in building energy management, contributing to a more sustainable and resilient future in energy use.

The paper is available at this link for download.

(Photo Credits: iStock)

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