Building simulation

Building Simulation increasingly proves to be a computer based calculation technique to estimate not only the energy performance, but also the non-energy behavior of buildings, building components and technical building systems. Computer modelling allows considering in particular the variability in time and in space of their operation, taking into account the contributions and interactions of all the different subsystems, and offering a detailed insight into the impact of different design options and of control strategies.

Until quite recent years, the main goal of simulation was to improve the understanding of some specific processes, of their interactions and of their effects on buildings and in particular on their energy efficiency (Spitler 2006). Much of the efforts focused on enhancing the detail discrimination and increasing the reliability of the results. The capability of describing accurately specific aspects of the behavior of the building was among the main concerns, so that development and validation of more accurate simulation codes was one of the first items in the agenda for building simulation researchers, developers and users.

Whole-building and multi-domain modelling, including energy systems, control strategies and occupant behavior has long been challenging. A hierarchical and sequential approach, from the envelope to the technical building systems or from energy to comfort analysis with the use of separate models and tools, was the common option.

Although not very frequent among practitioners, because of the high costs and the relatively modest user friendliness, building simulation has nevertheless provided a fundamental contribution in research. Due to the high complexity of the investigated system, its slow dynamic, and the long representative period characterizing the considered phenomena—dealing with weather conditions, seasonality and climatic features—virtual experiments in many circumstances were the only option to investigate the interactions between the indoor and the outdoor environment. Modelling has been particularly useful to compensate for missing experiments or to overcome the impossibility of getting enough experimental data or any data at all.

More recently, the tremendous enhancement of computing power and its widespread availability have dramatically increased building simulation possibilities, opening new perspectives and applications and ultimately fulfilling better the three main requisites for building simulation: high integrity representation, multi-domain modelling, and design process integration (Clarke and Hensen 2015).

Among the most significant trends, actually already announced and desired (Spitler 2006), multi-domain simulation is probably one of the most evident. Allowed by co-simulation approaches (Trčka et al. 2010), it has become more and more common not only in research but also in the professional practice. The possibility of coupling the simulation of thermal and lighting performance, considering envelope and systems, together with comfort aspects, has increased the capability of researchers and designers of analyzing the complexity of the indoor environmental interactions.

Multi-scale simulation has extended the analysis from the occupant (Yan et al. 2017) to the urban context (Allegrini et al. 2015), increasing details and accuracy, and including the different domains of investigations. At one end of the spectrum, behavioral models have been integrated in the simulation, introducing the human factor in the analysis and accounting for the impact of stochastic components. At the other end, microclimatic models have enabled a better contextualization of buildings in the urban areas, providing better awareness about reciprocal influence between buildings and the outdoor environment.

Parametric simulation has increased the possibility of investigating a broader range of configurations, enhancing the capability of identifying trends and highlighting strengths and weaknesses of specific solutions and technologies. Coupling parametric simulation with optimization techniques (Nguyen et al. 2014) allows the identification of the best design or operative configuration. In combination with multi-domain simulation, multi-objective optimization, including energy, cost and comfort performance is then possible. Design is not the only application, since optimization is used also in calibration of simulation models for existing buildings, useful to select optimal retrofit solutions. Moreover, real time optimization is at the core of model predictive control strategies (Killian and Kozek 2016), in which the building model is used to identify and update the best control strategy based on short-term weather and occupancy forecasts.

Finally, an interesting trend is related to the integration of design tools and building simulation tools (Negendahl 2015). This allows the designers to have a performance feedback directly in the native design tool and to make a more aware choice. It also gives an easier access to building simulation to non-experts, helping the diffusion, if not of the simulation practice itself, at least of the simulation results and capabilities.

Nevertheless, some concerns are rising together with the improvement and diffusion of building simulation, since more detailed simulation also means that a larger number of calculation parameters and more circumstantiated hypotheses are needed. On the one hand, this requires more expertise to get reliable outcomes, while on the other hand it may enhance the uncertainty sources. In this respect, there is an increasing need for opportunities for discussion and for education approaches to strengthen the collaboration between research and practice. That is why the International Building Performance Simulation Association, with more than 4000 members and 28 regional affiliates, is promoting events and conferences to enhance the awareness and knowledge in the use of building simulation (Clarke 2015), getting involved not only academics but also practitioners. One of these is the bi-annual conference organized by IBPSA-Italy, Building Simulation Applications (BSA). In the last edition, in 2017, it gathered more than 100 participants, with 77 papers. In addition, besides researchers, it also hosted a half-a-day special round-table about potential and limitation of a set of simulation tools, attended by about 80 practitioners, and a simulation introductory school, for 35 students from all over Italy.

Some of the works presented at BSA 2017 have been invited to appear as extended papers in this special issue, together with some additional contributions relevant to the topic.

As concerns building simulation development or use to design evaluation and optimization, Maalouf et al. investigate the performance of sustainable materials produced from natural resources and hemp-concrete or from recycled-waste non-biodegradable materials. Façades employing different materials, with different orientation and window size, and in different climates are analysed in terms of cooling, heating, and ventilation energy demands.

The article by Zhou and Zhang presents a numerical model to investigate the effect of grout thermal conductivity and heat capacity on the heat transfer performance of borehole heat exchangers. The numerical model is validated through sandbox experiments.

Zarrella et al. compare two different approaches to simulate borehole heat exchanger for ground source heat pumps, the g-functions method and a recent finite difference algorithm, the capacity resistance model. The comparison consists in a long-term hourly analysis of heating and cooling loads of a real office building, located in Italy, characterized by an appreciable imbalance between the energy exchanged with the ground in summer and in winter.

The article by Lin et al., deals with the energy saving potentials from variable refrigerant flow systems. A new energy saving control strategy and a new variable refrigerant flow system with chilled water storage are theoretically investigated. Simulation is carried out on a validated thermodynamic variable refrigerant flow model in EnergyPlus to assess the energy saving potential from both measures in different cities.

As regards optimization and multi-domain analysis, the article by Ferrara et al. considers the energy-optimization versus the cost-optimization design of multi-family buildings. Different technology scenarios and design alternatives are assessed and compared through dynamic simulation in northern Italy climate.

The article by Atzeri et al. analyses the integrated performance of different glazing systems coupled with different control approaches for roller shades. The global performance of shading controls, in terms of visual and thermal comfort, and primary energy demand for heating, cooling and lighting is evaluated by means of dynamic simulation.

Finally, dealing with the design integration of building simulation, Konstantzos et al. present a synthesis of the most recent metrics (visual comfort autonomy (VCA), lighting energy use, and view clarity) for assessing the visual environment performance of spaces with roller shades, in the form of an integrated framework and an alternate, interactive web-based tool. This tool allows selecting fabric properties based on different priorities: outside view, energy performance, or a balanced approach, all under visual comfort constraints.