Optimization Research of AI+Digital Twins in Building Equipment System

Abstract

Under the macro background of actively responding to climate change and promoting the “double carbon” strategy, the construction industry, as a key field of energy consumption and carbon emissions, has become a trend of green and low-carbon transformation. The operation efficiency of building equipment system, especially HVAC, electrical lighting and water supply and drainage system, directly determines the overall energy consumption of the building. This study focuses on the frontier technology integration of “ai+digital twins”, and explores its application and implementation path in the optimization of building equipment system. Through systematic literature review, the application status of digital twins and AI technology in the whole life cycle of building equipment design, construction, operation and maintenance is summarized. Through the case analysis of multiple scenarios, the energy efficiency improvement ability and carbon emission reduction benefits of the technology in typical scenarios such as commercial buildings, factories, municipal water supply networks are quantitatively evaluated. Finally, based on the comprehensive research data and AI intelligent analysis, a set of “technology economy policy” collaborative transformation path covering technical standards, business models and policy incentives is constructed, which provides an operable solution for the implementation of the “double carbon” goal in the construction field.