A framework to create bottom-up energy models that support policy-design and decision-making of electricity end-use efficiency: A case study in residential buildings and the residential sector
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In this work we present a framework that guides the creation of bottom-up energy models (BUEMs) that aim to support policy design of electricity end-use efficiency. Energy models are decision-making tools for policy-makers and they are key tools to evaluate decisions. However, research reveals that bottom-up energy models are empirically created and they are not designed to guarantee support towards policy design. Likewise, the use of scenarios has not been applied as a standard technique within BUEMs. Thus, is it possible to align these models to specific policy goals and standardize the use of scenarios in them through the application of a process? The framework proposed in this work includes phases, processes, and artifacts that conduct the modeler through the model's construction process. The processes incentive best practices for policy design for the residential sector and residential buildings. To build the proposed framework, we first research the characteristics of BUEMs and their opportunity areas. Then, we propose processes that are important for the model's design but we consider the application of best practices to overcome the problems encountered in the models. After that, we execute the framework and record all the events for future analysis. To finish, we assess the process execution quantitatively and qualitatively using the process mining technique. The results of the framework's application are promising by outperforming other methodologies in the literature. In fact, it has been proved that model's creation time can be diminished with the application of the framework. Likewise, the framework promotes: (1) policy alignment from the start to the end of the model's development process and (2) the definition of scope boundaries. Moreover, it brings transparency to the process by the use of the proposed templates. On the other hand, the utilization of the process mining technique to create a process model has brought advantages as well. For instance, (1) it is possible to monitor, control, and enhance the model's construction process and (2) The processes compliance can be evaluated and adaptations can be recommended with quantitative evidence.