A technical framework analysis of digital twin control algorithms for HVAC-BMS Integration and implementation challenges for Malaysian green buildings

Digital Twin technology offers transformative potential for integrating Heating, Ventilation, and Air Conditioning (HVAC) systems with Building Management Systems (BMS) in Malaysian green buildings. While proven effective in temperate regions, its application in tropical climates presents unique challenges, including high humidity, intense solar radiation, and consistently elevated temperatures. This paper examines current trends and prospects of Digital Twin applications in HVAC-BMS integration for Malaysian green buildings, focusing on implementation status, climate-specific adaptations, and potential benefits. Using PRISMA methodology, 36 articles published between 2020 - 2024 were systematically reviewed, analysing implementation frameworks, energy optimization strategies, and security considerations. Findings reveal that Model Predictive Control (MPC) algorithms achieve a 35.9% improvement in coefficient of performance compared to conventional Proportional-Integral-Derivative (PID) controllers, with energy consumption reductions of 23% - 30% across various building types. MPC-based Digital Twins demonstrate superior temperature control accuracy (± 0.4 C vs. ± 1.8 C) and humidity control precision (± 2.3 % RH vs. ± 7.5 % RH) compared to conventional systems. Implementation assessment reveals that GBI-certified buildings achieve significantly higher adoption rates (28%) compared to non-certified buildings (7%), with maturity levels primarily ranging from 1 to 3 on the 5-level framework. Break-even points typically occur between 2.2 - 3.1 years, with ROI averaging 120% - 150% over five years. Security implementation increased dramatically from 34% prior to 2022 to 87%.