Abstract
The planning process of nearly Zero Energy Buildings (nZEB), as defined in Energy Performance of Buildings Directive (EPBD), requires that designers check their solutions at all stages of planning. In the initial design phase, methods and tools for which only basic design knowledge of the modelling of energy efficiency indicators is required are often sufficient. With the introduction of fast modelling techniques, designers’ work can be simplified. A method and software for the fast modelling of nZEB energy efficiency indicators of buildings constructed with advanced multi-layer glass and building integrated photovoltaics facade (BIPV) structures are presented. The computer tool for fast modelling combines (i) upgraded national certificated software for energy performance of buildings (EPB) evaluation, which is used for performing auto-repeating numerical calculations based on the design of experiments (DOE) and (ii) software for the determination of multiple linear regression models and the presentation of results. The case studies made for different buildings and climate conditions show the variety of options offered by the developed fast modelling approach. It can be seen that buildings with a large proportion of advanced glassed facade and even all-glass buildings can fulfil nZEB requirements via the on-site production of electricity with BIPV facade structures.
Highlights
Zero Energy Buildings were introduced by the Energy Performance of Buildings Directive (EPBD) recast [1] as energy efficient buildings with high shares of the utilization of on-site or near-by renewable energy sources [2]
As we focused on the fast modelling of extended areas of glass facade structures, the energy demand for cooling has a significant influence on the buildings with extended areas of glass facade structures, the energy demand for cooling has a nearly Zero Energy Buildings (nZEB) metrics and, the set point temperature for cooling was selected as a P12 parameter
The evaluation tool was developed in the MS Excel environment because of built-in statistical functions needed for the design of multi-parametric regression models and the simple selection of parameters’ values in the process of building design evaluation
Summary
Zero Energy Buildings were introduced by the Energy Performance of Buildings Directive (EPBD) recast [1] as energy efficient buildings with high shares of the utilization of on-site or near-by renewable energy sources [2]. EU member states have introduced nearly Zero Energy Buildings (nZEB) metrics. By introducing nZEB requirements, the design of the building becomes more complex because energy efficiency evaluation must be part of the design in each planning phase. The earlier the design phase is, fewer details about the building are known, and only general knowledge of building modelling is typical for building designers. Inadequate solutions in the early design phases most often cannot be compensated by dynamic modelling by experts in the following phases, and any fixes are often very expensive. That is why the evolution of simplified buildings’ energy efficiency in early design phases remain useful and commonly used despite the various software for dynamic building thermal response modelling available on the market. Quasi-steady state modelling of yearly or monthly energy balances is characteristic for such calculation methods [3,4]
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