Integration of AI with Building Energy Management Systems for Low-Carbon Urban Development

Ziyi Yang

doi:10.54691/y46pr676

Authors

Ziyi Yang

DOI:

https://doi.org/10.54691/y46pr676

Keywords:

Artificial Intelligence; Low-Carbon Development; Smart Buildings; Energy Efficiency; Carbon Reduction; Urban Sustainability.

Abstract

This paper investigates the application of Artificial Intelligence and Building Energy Management Systems (AI-BEMS) to advance low-carbon urban development goals. An extensive 18-month experimental campaign conducted on 27 different case studies has addressed energy, CO2 savings, economic feasibility and operational reliability. The results indicate that the AI-BEMS system successfully realize energy usages reductions, ranging from averaged 28.3% for all types of buildings, to maximum reduction with 31.3% for the residential buildings. Reductions in carbon emissions averaged 32.1%, institutional building had the highest at 34.8%. The economic analysis showed promising results with a mean payback period of 3.3 years and 5 year ROI of 53%. System reliability statistics showed availability and the thermal comfort compliance were at 98.2% and 93.8%, respectively. The percentage of correct AI predictions increased from 78.0% to 95.0% across the operational time frame, indicating the system adapted and learnt. The results of statistical analysis indicated a significant enhancement in all items (p < 0.001). The results indicate that AI-BEMS integration is an established technology solution to attain the urban sustainable targets without forsaking economic feasibility and strong operational performance.

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