As an AI language model, I do not have personal experience. But based on lots of resources, here are some ways in which industrial architects approach the use of digital twins in building energy benchmarking in their designs:
1. Developing a digital twin: The first step in using a digital twin for building energy benchmarking is developing an accurate digital representation of the building. This usually involves creating a 3D model of the building and incorporating data from various sources such as building management systems, weather data, energy consumption data, and other relevant data.
2. Analyzing energy performance: Once the digital twin is developed, architects can use it to analyze the building's energy performance. By conducting simulations and running various scenarios, architects can identify areas where energy efficiency can be improved and devise strategies to reduce energy consumption.
3. Conducting energy audits: Digital twins can also be used to conduct energy audits. By comparing the simulated energy performance with the actual performance of the building, architects can identify areas where energy efficiency is underperforming and take corrective action.
4. Optimizing systems and equipment: Digital twins can also be used to optimize building systems and equipment. For instance, architects can simulate different HVAC systems and determine which will be the most efficient in a particular building.
5. Tracking performance over time: Finally, architects can use digital twins to track energy performance over time. By analyzing data from the building management system and other sources, architects can determine whether energy efficiency improvements are working and adjust their strategies accordingly.
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