# Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy
## 5 Digital Twin Technology for Energy Sector Development
### Software for Energy Prediction-Actual Software Cases
[84] used MATLAB and EnergyPlus for building modelling and energy analysis to compare comfort performance and cost control for a near-zero energy building in southern Italy. The research methods were model predictive control (MPC) and multi-objective genetic algorithms. The researcher used a framework of simulation and optimization for model predictive control of space cooling systems. The optimization problem was solved by running a genetic algorithm (a variant of NSGA II) in a MATLAB environment. The objective function was evaluated by coupling MATLAB and EnergyPlus. The results show that the approach of combining model predictive control with different thermal comfort models can result in some cost savings while maintaining similar comfort performance. [PERSON] et al. [94] used EnergyPlus with an optimization algorithm to optimize the design of a conventional house in northeast India based on building energy simulation results. [PERSON] et al. [111] used EnergyPlus and genetic algorithms for energy simulation and optimization of a residential building in Hong Kong under extreme weather conditions. The study introduced a new modelling strategy to investigate and compare actual building performance under different cooling supply scenarios applied to a high-rise residential building under near-extreme weather conditions. The conclusions show that this combined operation can assist in the use of fan strategies. As well as certain design factors can provide opportunities to reduce total cooling energy in near-extreme weather conditions. [PERSON] et al. [55] used EnergyPlus and PMfserv for building modeling and energy analysis. PMfserv was used to develop models of occupant behavior that take into account physical comfort and psychological states. The research methodology involved developing and validating an occupant behavior model based on existing buildings and coupling it with a conventional building energy model. The coupling of the models was achieved by using BCVTB as a bridging procedure. It is concluded that the coupled simulation experiment integrates the agent-based resident behavior model with the building energy model in EnergyPlus, providing a comprehensive assessment of building performance through a multi-perspective analysis. Key findings include that occupant behavior influences energy use throughout the building from the room level that thermal comfort is not the only driver, and that occupant behavior leads to multifaceted changes in the built environment. [PERSON] et al. [57] used EnergyPlus and jEPlus + EA software for building energy modeling and optimization, with the NSGA-II algorithm used to perform the optimization. The study focused on buildings in Iran and used a multi-objective simulation-based optimization approach to control blind specifications to reduce energy consumption and thermal visual discomfort. The results show that different control strategies and building specifications significantly affect energy consumption and comfort. For example, in Tehran, the optimal strategy included setting the first point at 17.8 \({}^{\circ}\)C, using internal shading positions and slat reflectivity of 0.46, with an annual electricity consumption of 2340 kWh, DGI of 0.9, and PPD of 6.9%. The study concludes that the use of a controlled blind's specification can significantly reduce energy consumption and improve thermal and visual comfort in buildings, with the optimum specification varying by location and climate. The article discusses research related to shading systems and lighting performance control and highlights the application of automated shading and lighting systems to improve energy performance while exploring the impact of different control strategies and building codes on energy performance and comfort and highlighting the importance of selecting the best shading features and physical characteristics according to climatic conditions. [PERSON] et al.