Interaction between a Cyclically Heated Building and the Ground, for Selected Locations in Europe

Abstract

The aim of the study was to verify the impact of the location of a cyclically heated building on its energy needs and interaction with the environment. The model building was a large-scale broiler house located in southern Poland. In the examined facility, year-round measurements of selected parameters of the internal and external microclimate were carried out. The tests also covered the temperature of the soil in three measurement columns. The obtained measurement results were used for further computer analyses. A geometric model of the building was made and a calculation model specification was introduced, supported by specialized software for the physics of WUFI®plus structures. The numerical analysis included validation. The validation results were assessed on the basis of the Coefficient of Determination method (R2) and the Goodness of Fit (GOF) method. Due to the lack of normality of the data distribution, a Rang-Spearman correlation analysis was carried out, which showed a very strong data correlation (0.94). The analysis of the R2 coefficient of determination confirmed the high reliability of the model (83%). In the case of the GOF method, a compliance value of 87% was obtained. Differentiated locations were adopted for further analysis, while maintaining the structure of the examined building in reality. Six European locations were selected: Kraków (Poland), Málaga (Spain), Brest (France), Visby (Sweden), Umea (Sweden), and Kiruna (Sweden). The analysis included three variants, in which the length of the technological break was adopted accordingly. A technological break between production cycles was assumed, the three variants of which lasted 3, 7, and 14 days. The analysis of the obtained results showed that the external microclimate significantly determines the energy interaction between the building and the ground. The length of the technological break is very important in a climate dominated by low temperatures (Northern Scandinavia). The south-western part of Europe allows the technological break to be extended without significant differences for heating purposes. The length of the technological break in the range of 3 to 14 days does not significantly affect the intensity of heat exchange with the ground on a yearly basis, regardless of the location of the building. There were differences of no more than 2% between the technological break lasting 3 days and the 14-day break.

Development, Validation, and Application of Building Energy Simulation Models for Livestock Houses: A Systematic Review

“…Table 4 also highlights the number of data (sample size) that were adopted for the validation and for calculating the GoF indexes together with the duration of the validation period. As visible from the table, the duration of the validation period is remarkably different amongst the analyzed works and ranges between 48 h [41] and one year [45,55]. The sample size used for the validation of the indoor climate conditions (θ air_i and φ air_i ) is usually higher than the ones used for the validation of energy parameters (E H and E fan ).…”

“…Another application of BES models is the energy assessment with different focuses. For example, BES models are used to estimate the thermal loads of the livestock house, as performed by Qi et al [44], Nawalany and Sokołowski [45], and Izar-Tenorio et al [46]. In other cases, energy assessments are performed for evaluating energy efficient solutionsas performed by Kwak et al [20] and Jackson et al [16]-with a specific focus on the envelope, as in Costantino et al [17], Axaopoulos et al [47], and Wang and Xue [48].…”

“…Lee et al [59] Duck house (N) Biosystems Engineering Shin et al [43] Piglet house (M) Biosystems Engineering Costantino et al [31] Fattening pig house (M) Applied Energy Nguyen-Ky and Pentillä [60] Dairy barn (N) Applied Engineering in Agriculture Lee et al [42] Duck house (M) Biosystems Engineering Costantino et al [63] Broiler house (M) Energy and Buildings Hamilton et al [64] Broiler house (M) Advances in Mechanical Engineering Liberati and Zappavigna [41] Generic house (N/M) Transactions of the ASABE Silva et al [65] Broiler house (M) Revista Brasileira de Engenharia Agrícola e Ambiental Wagenberg et al [66] Fattening pig house (M) Biosystems Engineering Schauberger et al [67] Fattening pig house (M) International Journal of Biometeorology Cooper et al [40] Generic house (N/M) Journal of Agricultural Engineering Research Energy assessment Si et al [49] Fattening pig house (M) Science of the Total Environment Qi et al [44] Nursery + fattening pig house (M) Agriculture Nawalany and Sokołowski [45] Broiler house (M) Energies Costantino et al [17] 1 Broiler house (M) Journal of Cleaner Production Kwak et al [20] 2 Piglet house (M) Energy Strategy Reviews Panagakis et al [68] 1 Broiler house (M) CIGR Journal Costantino et al [69] Broiler house (M) Biosystems Engineering Izar-Tenorio et al [46] Broiler house (M) Journal of Cleaner Production Wang et al [57] Laying hen house (M) Computers and Electronics in Agriculture Jackson et al [16] Fattening pig house (M) Biosystems Engineering Jackson et al [70] Fattening pig house (M) Energy and Buildings Axaopoulos et al [47] 1 Fattening pig house (M) Transactions of the ASABE Wang and Xue [48] 1 Piglet house (N) Transactions of the ASABE Zhao et al [58] Laying hen house (M) Biosystems Engineering Menconi et al …”

“…Besides E+ and TRNSYS, three other ready-to-use simulation tools were used in the framework of the analyzed works, as visible in Table 3. Nawalany and Sokołowski [45] adopted WUFI plus [82], Nguyen-Ky and Pentillä [60] adopted IDA Indoor Climate and Energy (IDA ICE) [83], while Wang et al [57] preferred to use Designer's Simulation Toolkit (DeSt) [84]. The simulation time steps adopted in ready-to-use simulation tools are generally shorter than in customized models, ranging between five minutes and one hour, as visible from the works of Cho et al [73] and Shin et al [53], respectively.…”

“…In other cases, the thresholds are defined in the work itself, without referring to the previously mentioned documents. This second approach is adopted, for example, by Nawalany and Sokołowski [45] and Silva et al [65]. Nawalany and Sokołowski [45] set the thresholds for the coefficient of determination (R 2 ) and the Goodness of Fit (GOF) at values higher than 75% and 80%, respectively.…”