Nowadays, there is growing interest in all the smart technologies that provide us with information and knowledge about the human environment. In the energy field, thanks to the amount of data received from smart meters and devices and the progress made in both energy software and computers, the quality of energy models is gradually improving and, hence, also the suitability of Energy Conservation Measures (ECMs). For this reason, the measurement of the accuracy of building energy models is an important task, because once the model is validated through a calibration procedure, it can be used, for example, to apply and study different strategies to reduce its energy consumption in maintaining human comfort. There are several agencies that have developed guidelines and methodologies to establish a measure of the accuracy of these models, and the most widely recognized are: ASHRAE Guideline 14-2014, the International Performance Measurement and Verification Protocol (IPMVP) and the Federal Energy Management Program (FEMP). This article intends to shed light on these validation measurements (uncertainty indices) by focusing on the typical mistakes made, as these errors could produce a false belief that the models used are calibrated.
Building energy performance (BEP) is an ongoing point of reflection among researchers and practitioners. The importance of buildings as one of the largest activators in climate change mitigation was illustrated recently at the United Nations Framework Convention on Climate Change 21st Conference of the Parties (COP21). Continuous technological improvements make it necessary to revise the methodology for energy calculations in buildings, as has recently happened with the new international standard ISO 52016-1 on Energy Performance of Buildings. In this area, there is a growing need for advanced tools like building energy models (BEMs). BEMs should play an important role in this process, but until now there has no been international consensus on how these models should reconcile the gap between measurement and simulated data in order to make them more reliable and affordable. Our proposal is a new generation of models that reconcile the traditional data-driven (inverse) modelling and law-driven (forward) modelling in a single type that we have called law-data-driven models. This achievement has greatly simplified past methodologies, and is a step forward in the search for a standard in the process of calibrating a building energy model.
Building information modelling (BIM) is the first step towards the implementation of the industrial revolution 4.0, in which virtual reality and digital twins are key elements. At present, buildings are responsible for 40% of the energy consumption in Europe and, so, there is a growing interest in reducing their energy use. In this context, proper interoperability between BIM and building energy model (BEM) is paramount for integrating the digital world into the construction sector and, therefore, increasing competitiveness by saving costs. This paper evaluates whether there is an automated or semi-automated BIM to BEM workflow that could improve the building design process. For this purpose, a residential building and a warehouse are constructed using the same BIM authoring tool (Revit), where two open schemas were used: green building extensible markup language (gbXML) and industry foundation classes (IFC). These transfer files were imported into software compatible with the EnergyPlus engine—Design Builder, Open Studio, and CYPETHERM HE—in which simulations were performed. Our results showed that the energy models were built up to 7.50% smaller than in the BIM and with missing elements in their thermal envelope. Nevertheless, the materials were properly transferred to gbXML and IFC formats. Moreover, the simulation results revealed a huge difference in values between the models generated by the open schemas, in the range of 6 to 900 times. Overall, we conclude that there exists a semi-automated workflow from BIM to BEM which does not work well for big and complex buildings, as they present major problems when creating the energy model. Furthermore, most of the issues encountered in BEM were errors in the transfer of BIM data to gbXML and IFC files. Therefore, we emphasise the need to improve compatibility between BIM and model exchange formats by their developers, in order to promote BIM–BEM interoperability.
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