Understanding the Three Types of Energy Models for Buildings
Simply by looking at the nameplate data and functioning program of a building, we can easily estimate its energy consumption. One important thing to note here is that the link between various building systems and the local climate is not taken into account when doing this estimation. Energy modeling is a very important tool when trying to decide between energy efficiency and measures for a building project.
A comparison between the energy savings accomplished in buildings was made during a study by the American Institute of Architects. The comparison was made with energy modeling the first time and without it the second time. More than 35% of savings were accumulated by owners who used energy efficiency measures without modeling, while those who included modeling in their schedule achieved more than 50% savings. It is obvious building owners who used energy modeling achieved better results.
According to the method used to process the information, we can classify energy models into three main types: grey-box, black-box, and white-box. Energy models are not the only ones using this classification since it is normally used by data scientists.
Let’s explain these three categories:
- White-box – Physics laws stand at the ground of this model, and the property of the system being model.
- Black-Box – Historical data and statistical analysis create this second model.
- Grey-box – A mix of historical data and simplified physics is used in this model.
DOE-2 and EnergyPlus are just a couple of software that use physics-based models due to their increased accuracy. Nonetheless, due to the fact that there are lots of equations and data involved, we can that white-box models demand a lot of work. The simulation of this model can also be quite demanding on computer resources due to its complexity.
Historical data are not required in order to accomplish this model, so this is another important advantage for the white-box. For building owners who know the physical properties of their construction, it will be very easy to simulate this model with high accuracy. Real estate developers can obtain important insights with the help of white-box energy models, especially if engineering knowledge and computing power are available.
The black-box model is very different from the white box due to the fact that it is based on reverse engineering with existing data. Apart from the fact that the processing time is smaller compared to the white-box models, the black box can be calibrated easily with the available data. Artificial neural networks, support vector machines, and statistical regression would be a couple of examples of modeling methods that use data.
The need for historical data would be the main drawback of this model. Such models can be applied only to buildings that generate the data, or other buildings with nearly the same properties. If no data can be used to calibrate the model, we can say that it is nearly impossible to create a black-box model.
The reason why this model is called grey-box would be the fact that it contains elements from both black and white-box models. While white-box models require complex physics equations in order to provide the best results, grey-box models use easy physics equations. As soon as they are calibrated, grey-box models can be simulated faster.
This is done at the expense of higher accuracy. In order to increase the accuracy, grey-box models are calibrated with historical data. Speed and accuracy are combined in this model, so this is why it is called grey-box, simply because it is a combination of white and black box models.
Considering the fact that the simulation parameters are configured until the results of the model will match the behavior of the system being model, we can say that the process of calibrating black-box and grey-box models can be considered a “training” process.
How to use energy modeling for better results
Considering the fact that all models can be applied in the building sector, we can’t say that one is better than another. If no data is available, it is recommended to use the white-box model. If we think about the physics principles, we can say that these models can be used to compare the real behavior of a building with its ideal behavior. In case you want to predict the energy consumption of a building or to represent it, you will need to use the black or grey-box model.
Due to the fact that the Local Law 97 of 2019 in New York will limit energy modeling from 2024, we can say that each and every model is useful for NYC building owners. Building owners should make sure that they locate the proper mix in order to reduce emissions since there are loads of different options to upgrade buildings.
When thinking about the advantages of connecting to the system versus building, operating, and maintaining their own building thermal system, the cost will always play an important role in the final decision. Other important aspects for future customers are the reliability of district energy together with the ability to free up valuable building real estate. We can say that nowadays customers are paying close attention to the overall efficiency of district energy, compared to other options.
Various strategies are used by district energy systems. They include combined heat and power production, thermal energy storage, and renewable energy use. The benefits of all these aspects are taken into account when trying to make an informed decision. Energy models are being used to recognize and see the full potential of all these benefits.