# Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy
## 4 Energy and Its Digital Transformation
### Digitalization in Building Energy Management  
At the end of the 20 th century, the third industrial revolution was characterized by the widespread use of computers and the Internet, laying the foundation for new building energy management technologies [21]. Computer simulation optimization has been introduced into energy management, and various energy simulation programs have gradually emerged. Building Energy Modelling (BEM) has become increasingly popular as the application of energy simulation programs which has proven effective in improving energy efficiency. The study used computer simulations to optimize integrated lighting, passive solar heating and cooling, and energy efficiency strategies in building design. The results showed a 50% to 70% reduction in building energy consumption compared to code requirements [39]. Different energy simulation programs were incorporated during that time to meet different user needs. Most programs are equipped with capabilities for building modelling, renewable energy systems, electrical systems and equipment,HVAC systems and equipment, environmental emissions, economic evaluation, and user interface [40]. We are currently living through the Fourth Industrial Revolution, with the combination of BIM and Building Energy Modelling (BEM) being expected to collaborate with other advanced technologies, such as the Internet of Things (IoT), to improve the efficiency of energy simulation further. Combining these methods for real-time simulation is a future priority for Industry 5.0. Sensors, big data processing techniques, and deep machine learning are expected to be included for better simulations and energy forecasts [23; 41; 42]. Digital transformation is driving the energy industry through the Fourth Industrial Revolution [21], and the application of various digital management of energy systems has had a positive impact, such as smart meters, advanced control systems, artificial intelligence, and deep learning algorithms. Building Information Modelling (BIM) has also emerged as a potential solution to improve energy efficiency. Digital representations of construction processes through BIM platforms can facilitate information exchange and interoperability in digital formats. The Architecture, Engineering, Construction and Operations (AECO) sector is one of the primary sources of global energy consumption and its negative impact on the environment cannot be ignored. Energy use in residential and commercial buildings has continued to increase by up to 40% [37]. Therefore, reducing the energy demand for Sustainability is crucial. Section 3.3 explains that digital twin technology can potentially improve buildings' energy efficiency. It is generally accepted that incorporating digital twins into the entire energy management lifecycle of building design can positively impact the design process and final design [34]. Recent research on the application of digital twins in building energy mainly falls into two categories: one focuses on using sensors and BIM software to visualize better and control energy consumption. The other category is more focused on using artificial intelligence to predict future energy demand to optimize building energy system management efficiency. Optimizing electrical, heating, and cooling loads (HVAC systems) is critical to building energy management. From the results of these two types of research, there are three main ways to apply the digital twin method to building energy management optimization: First, the digital twin can monitor and analyze real-time data from sensors installed in the building to determine whether energy consumption can lower area. Second, the digital twin tests and evaluates the impact of different energy management strategies on the building's energy consumption. Third, digital twins help managers make informed decisions about energy use and identify energy-saving opportunities.