## 2 Building Energy Retrofitting
### Building Energy Models and Tools for Retrofit Applications  
The process of enhancing building energy efficiency and making decisions regarding energy retrofitting involves an optimization method aimed at selecting technically advantageous and cost-effective measures. In this decision-making process, the building energy model plays a crucial role in accurately characterizing the actual building and simulating various alternatives, scenarios, and improvement measures in a robust and flexible manner. Different modeling approaches can be categorized as white-box, grey-box, and black-box. These approaches vary in terms of the level of physical relationships incorporated into the models. White-box models are fully physics-based, where every detail of the building is known [19]. They are predictive models that can be clearly explained in terms of their internal mechanisms. In building applications, white-box models are widely used in the form of simulation software such as EnergyPlus, eQUEST, DOE-2, ESP-r, BLAST, and TRNSYS, among others. These models are highly detailed and comprehensive, providing a flexible approach to assessing the retrofit potential of building systems or technologies. White-box models rely on building physics, whereas black-box models are data-driven and utilize data collected from various building meters and sensors [20]. Black-box models are systems that are analyzed based on their inputs and outputs without any knowledge of their internal workings. These models were extensively used in the building domain for fault detection, diagnosis, and building system control, leveraging their classification and prediction capabilities. Successful applications include timely detection and prediction of faults in heating/cooling cycles, appliances, lighting energy use, and changes in indoor environmental conditions [21]. On the other hand, grey-box models offer a balanced hybrid approach to building energy modeling. These models incorporate physics equations to represent building behavior, but the equations are simpler compared to those used in white-box models [22]. As a result, grey-box models can be simulated more quickly. They combine a partial theoretical structure with measured data to complete the model, aiming to closely represent the thermal behavior of a building. However, the simplified physics in grey-box models result in a loss of accuracy, which is compensated for by calibrating the model with data, similar to the black-box modeling approach. Various countries, both in the public and private sectors, developed a wide range of decision-making tools for energy retrofit applications. These tools aim to facilitate investments in energy efficiency measures by offering information on suitable energy improvement solutions tailored to specific cases. Examples of such tools include the online tool called 1 2 3 Reno [23], which was developed as part of the European project MARIE. This tool enables the assessment of energy improvement packages based on different renovation objectives and various types of homes in the Mediterranean and alpine regions of France. Another tool, the Quickscan tool [24], was created as part of the European-funded Interreg NWE ACE-Retrofitting project. It provides an initial overview of retrofit measures that could be implemented in each building. The Home Energy Check (HEC) [25], developed as part of the Request2 Action project, allows Greek homeowners to simulate the energy performance, rating, and CO2 emissions of their homes. In the United States, different tools were developed, such as the Home Energy Yardstick [26] and MyHomeEQ [27]. These tools aim to motivate and inspire homeowners by enabling them to compare their home's energy usage with similar homes in their region and providing information on energy improvement possibilities. Denmark has its own tools as well, such as Totalkredit's energy calculator [28], developed in collaboration with the Danish Energy Agency.