# Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy
## 6 Challenges and Future Directions  
### BEM Software  
Energy simulation software is widely used nowadays, such as EnergyPlus, but they have a series of challenges and limitations in its use. First, a common limiting factor in research is model uncertainty due to its internal complexity, resource constraints during simulation, and the lack of components [84; 104]. Furthermore, this simulation software is relatively complicated to operate. It is not friendly to new users, which can easily lead to their misuse, thus further increasing the uncertainty and error of the model [102; 105]. COVID-19 has also had a profound impact on global energy consumption. Differences between actual energy consumption and modelled energy results are becoming increasingly significant [187]. At the same time, although increasing the number of simulation runs can improve the accuracy to a certain extent if the number of iterations is increased too high, it may negatively affect the accuracy of the final data analysis results and increase the error rate [64].  
In addition, such simulation software may ignore some critical factors in the simulation process. For example, in-depth studies of the calorific value of building structures [64], human actions such as improper temperature set points, and improper HVAC system design and operation [75]. In using tools such as Revit, for example, the HVAC system cannot be created, and an existing HVAC system needs to be selected from the software library [51].  
New building design challenges, such as unconventional wall designs and properties and complex building material properties, may also increase the difficulty of simulation, leading to inaccurate simulation results [79]. Finally, in the energy investment decision problem, the diversity of assessment tools makes it possible to analyze all sustainabilityaspects. However, the diversity of methods only sometimes leads to consistent assessment results [81].  
In general, although the use of energy simulation tools provides essential support for building design and energy decision-making, in practical applications, due to various factors, data needs to be cleaned and processed more carefully to reduce simulation errors [90].  
Several vital areas need to be focused on for the future directions of energy simulation software. First, the energy performance analysis of the building life cycle can be explored in more depth, including building material parameters and the role of different cooling loads in the energy performance analysis [62]. This may require varying the thermal properties of building materials to study the impact of this parameter on building energy consumption [64].  
Second, a more detailed study of the layout and configuration of buildings is also a meaningful direction. This may include looking at random layouts of buildings and considering factors such as shading devices for different buildings [58]. At the urban scale, the use of 3D GIS for urban energy planning, the study of building heating and cooling energy requirements, and the consideration of building retrofits and climate change are future research priorities [90].  
Determining the weight of the objective function according to the city's climatic conditions also requires further study [74]. As for the energy system, it can be considered to promote the use of renewable energy systems, conduct more energy consumption analysis, and in practical applications, develop a thermal energy storage system to decouple the availability, demand of thermal energy, and improve the control function to improve Efficiency of the system in cities with different climates [74,102].  
Finally, new research and development also require continuous testing and validation to ensure new methods' validity [105]. In general, the future development of energy simulation software will pay more attention to a comprehensive analysis of building life cycles, more detailed architectural and urban planning research, more diverse energy system analysis, and continuous method testing and improvement.