Classification of European Climates for Building Energy Simulation Analyses

Several studies couple simulations of building systems and statistical techniques in order to draw findings which can be generalized under given constraints. To this extent, one of the most important inputs to deal with is climatic conditions: indeed, the weather data and the localities chosen for the analysis can seriously affect the representativeness of the simulation outcome with respect to other regions. Nevertheless, the first question we should answer regards the domain to which one or few reference climates should be representative. As a common practice, national guidelines, heating and cooling degree-days scales and worldwide recognized climatic classifications are adopted. However, in some cases, these kinds of categorization are suitable only for specific applications. For example, the well-known and used Köppen-Geiger classification with the later Trewartha’s modifications is based on annual or seasonal air temperatures and cumulative precipitation and highlights mainly the relationship between climate and vegetation. Consequently, while this classification can be very effective to distinguish ecological systems, it can be insufficient for building energy analysis. Similar considerations apply to ANSI/ASHRAE 90.1 and 90.2 classification. In this work, we propose a critical discussion of the main climate classification system adopted in Europe and present a clustering and classification analysis on 66 European locations. The aim is to identify a limited number of climatic zones and, for each one, a reference climate to be used for energy simulations. The hourly weather data of dry bulb temperature, relative humidity and global horizontal irradiation reported in typical and reference years have been used as input. The clustering analysis has been performed with two approaches with different levels of complexity: (1) a simplified approach based on the calculated monthly averages of the weather variables and (2) a more detailed one based on the hourly profiles, through non-parametric techniques such as the Kolmogorov-Smirnov test. The obtained climatic classes have been compared to Köppen-Geiger traditional ones, underlining the main changes and the impact for building energy simulation analyses

Comparison Of Quasi-Steady State And Dynamic Simulation Approaches For The Calculation Of Building Energy Needs: Thermal Losses

One of the aims of the European Directive 2010/31/EU (formerly 2002/91/EC) is to reduce the energy consumption of buildings introducing an energy labeling protocol which is expected to capture the attention and reorient the market, sustaining the diffusion of more efficient solutions. In order to evaluate the building energy performance, either analytical approaches or enhanced simulation tools are allowed. The coherence of the methods is important in order to avoid misleading results which can affect the evaluation by the market and eventually compromise the Directive effectiveness. The European Standard EN ISO 13790:2008 suggests to use the dynamic simulation in improving and tuning the quasi-steady state method proposed, and in particular to refine the correlation used to calculate the utilization factors (i.e., the dynamic parameters which reduce the thermal gains for heating need calculation and the thermal losses for cooling). Many efforts in calibrating the EN ISO 13790:2008 led to some changes on the correlations proposed in order to adapt the method to the climatic conditions, especially for the cooling season, and the building stock’s characteristics in different countries, but large discrepancies have been found. Differently from the previous works, the authors analyze the discrepancy sources focusing firstly on thermal losses, instead of considering directly the final result in term of energy needs. In this paper, the deviations between the thermal losses are evaluated, by means of an extensive use of simulation, analyzing a set of a 960 configurations obtained by the factorial combination of different values for the building shape, envelope insulation and composition, window type and size, ventilation rate and climatic conditions. Six different setpoint conditions were considered for the simulations. The analysis allowed the authors to identify the relevance of the deviations and to suggest ways to improve the correspondence between simulation and quasi-steady state methods in tuning processes

Extensive Comparative Analysis Of Two Building Energy Simulation Codes For Southern Europe Climates: Heating And Cooling Energy Needs and Peak Loads Calculation In TRNSYS And EnergyPlus

In order to evaluate the energy performance of buildings, both in heating and in cooling periods, the simulation codes can be used. Moreover, in accordance with the technical Standard EN ISO 13790:2008, the simulation codes can be employed for refining the steady-state methods, and particularly the utilization factors estimations, in accordance with the procedure proposed. As the various simulation codes implement different capabilities and refer to different mathematical models and calculation assumptions, the necessary validation steps which are used for diagnostic purposes are not enough to ensure the agreement of the results over a wider range of configurations and conditions. The main dynamic simulation codes have been generally evaluated according to the Standard ANSI/ASHRAE 140:2007 (BESTEST). By this approach the user can choose a software among those successfully tested, giving acceptable deviations between the computed output and the reference values for a selected number of reference buildings defined in the Standard. However the number of those reference building configurations is limited and the considered features are not representative of the common building stock present for instance in Southern Europe. Moreover, as those configurations were selected for diagnostic purposes, they are expected to produce unacceptable biasing when considered with statistical approaches in order to improve the quasi steady state approaches as the one proposed in the technical standard EN ISO 13790:2008. In this work a procedure to identify the main causes of deviation has been developed and has been applied to two well-known dynamic simulation software: TRNSYS (version 16.1) and EnergyPlus (version 7). The approach is based on a factorial plan of comparison aimed to investigate the main variables related to the envelope of the building and its behavior: variations in geometry and boundary conditions (dimensions and orientation of the glazing, amount of dispersing surface) envelope characteristics (walls insulation and heat capacity, insulation and solar transmittance of glazings) internal gains. From the combination of the values of the above variables, more than 1600 different configurations have been obtained for two Italian climatic conditions, each of which providing monthly values for heating and cooling needs and for heating and cooling peak loads. Thanks to the large number of configurations, the monthly heating and cooling energy needs and peak loads have been analysed with inferential statistics, which allowed to evaluate the agreement between the outputs and to characterize the weight of the different variables in causing the deviations found

Development Of Climate Classification Through Hierarchical Clustering For Building Energy Simulation

Climate classification plays an important role for the identification of homogeneous groups of climates, from which representative locations can be extracted and used for building energy simulation analyses. Nevertheless, according to the current state-of-the-art, the main reference systems consider just a fraction of those weather quantities which are relevant in the building energy balance, i.e., ambient temperature and humidity and solar radiation. To overcome this issue, in previous researches a new methodology was defined, based on monthly series of weather quantities, statistical analyses and data-mining techniques for climate clustering. In this work, with the aim of further developing such approach, a shorter time-discretization of weather quantities, i.e., a weekly discretization, was tested, alongside additional variables describing the daily range of ambient temperature and humidity. In order to investigate the potential of those modifications, a dataset with more than 300 European reference climates was analyzed and subdivided into climate classes according to the proposed clustering procedure

Development of a shoeboxing approach for Urban Building Energy Modeling

Urban Building Energy Modeling aims at assessing the building energy performance at city scale with as little computational effort as possible. Thus, different methods have been developed in the last years to reduce the required calculation time by simplifying the modeling approach, selecting only representative buildings, or minimizing the building description. Starting from the latter ones, this work proposes a novel algorithm capable of abstracting a randomly shaped building into a representative shoebox. The presented shoebox generation algorithm is based on a preliminary sensitivity screening analysis on a set of reference parallelepiped-shaped thermal zones. This allowed the identification of the most significant geometry indicators influencing the building’s performance. Based on this, more complex geometries have been simplified to the shoebox with the same indicators and the accuracy of the algorithm has been evaluated comparing the simulated performance of simplified and original buildings. The approach includes the definition of equivalent shading surfaces, to account for self-shading elements in the original building geometry. The algorithm has shown good accuracy not only on the hourly thermal loads, but also the zones’ hourly temperature profiles, reducing to one third the energy simulation time with respect to the detailed building model. Although not as fast as other urban modelling approaches in the literature, it can retain accurate results at a finer time scale, i.e., on hourly basis, which is necessary in applications such as district heating and energy networks

Energy Performance And Long-Term Evaluation Of Internal Thermal Comfort Of An Office Building With Different Kinds Of Glazing Systems And Window Sizes

Although the presence of large window surfaces could be preferable during the heating season when solar gains through the glazed components can overcome heating losses from the same surfaces, during the cooling season more attention has to be paid in order to limit the inlet of solar radiation which causes the increment of cooling load. Generally the optimal tradeoff for energy optimization, as already underlined in a previous paper by the authors, is using low thermal transmittance and high solar factor glazing, even if higher solar transmittance considerably worsens the cooling performance. However, the choice of glazing type and the design of windows on a façade may depend on comfort consideration besides energetic evaluations. Thermal sensation of an individual is mainly related to the whole thermal balance of the human body. Comfort limits can in this case be expressed by two indexes proposed by Fanger in 1970: the Predicted Mean Vote, PMV, and the correlated Predicted Percentage of Dissatisfied, PPD. The PMV depends on four environmental parameters (air temperature, air humidity, air velocity and mean radiant temperature) and two variables connected with human being (physical activity and clothing). The air temperature, the air humidity and the air velocity inside a building are directly under the system control. In contrast, the mean radiant temperature is strongly conditioned by the envelope surface temperature, and in particular, by the presence of glazed surfaces whose insulating performance is lower than the opaque components one. In this paper the study of heating and cooling energy needs of an open-space office with different windows’ characteristics has been carried out controlling the internal comfort conditions with appropriate setpoint of the system. An office module with windows on a single façade, or on opposite façades, oriented towards 3 different orientations has been simulated, varying the glazed area (2 sizes), the glazing systems (4 types) and considering three localities of central and southern Europe. The PMV have been calculated for each hour of occupation of the whole year assuming two season as regards the setpoint conditions and clothing level. Calculations have then been repeated considering also the effect of the diffuse and beam solar radiation through the windows directly reaching the occupants. The evaluation of the long-term comfort conditions (on seasonal basis) has been conducted considering some statistical indicators of distribution (the median, minimum, maximum and the interquartile range) and the energy performance of the different glazing solution have been compared accounting for the comfort one

Influence of the representativeness of reference weather data in multi-objective optimization of building refurbishment

Energy saving measures properly applied to the existing building stock can bring noticeable savings. In particular, optimal cost-effective solutions can be found through multi-objective optimization techniques, such as those based on genetic algorithms (GA), coupled with building energy simulation (BES). Although the robustness of GA multi-objective optimizations to the quality of the inputs is discussed in the literature, the role of the weather data file is not investigated in detail. For this reason, this work analysed the extent to which the method adopted for the development of reference weather data for BES can affect the optimal solutions. Considering a group of simplified building configurations and the location of Trento, Italy, many multi-objective optimizations are performed. The results show changes to both Pareto fronts and optimal retrofit solutions