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Article

Enhancement of Thermal Comfort and Energy Performance of Educational Buildings in the Warm Season: The Case Study of Two Public Schools in Bolzano, Italy

by
Angelica El Hokayem
,
Giovanni Pernigotto
* and
Andrea Gasparella
Faculty of Engineering, Free University of Bozen-Bolzano, 39100 Bolzano, Italy
*
Author to whom correspondence should be addressed.
Energies 2025, 18(17), 4483; https://doi.org/10.3390/en18174483
Submission received: 3 August 2025 / Revised: 18 August 2025 / Accepted: 19 August 2025 / Published: 23 August 2025
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Abstract

Most educational buildings in the north of Italy, whether of dated or recent construction, were designed to comply with the thermal comfort and energy performance requirements set for the heating season due to limited use in the summer months. In the latest years, however, with greater frequency, school buildings have been used to host indoor summer activities, and, due to the warm temperature conditions and heat waves, indoor thermal discomfort is often experienced, with negative impacts on occupants’ task performance. Consequently, the need to guarantee adequate indoor thermal comfort in schools in the warm season is becoming a growing concern for local public authorities. In this context, this work examines a set of strategies for the enhancement of the energy performance and indoor thermal comfort of public school buildings in the cooling season. Thus, two case study public school buildings of dated and recent construction located in Bolzano, Italy, were analyzed and compared. This study shows the potential of passive and semi-passive measures in improving indoor thermal comfort in the spring–summer months and the limit beyond which mechanical cooling and ventilation systems are required to ensure adequate levels of indoor environmental quality and task performance in the warmest months.

1. Introduction

In Italy, a large part of the educational building stock has been conceived to guarantee thermal comfort conditions in the fall–winter seasons, complying with the requirements set for the heating season due to their limited use in the summer months. However, in the latest years, school buildings have been used to host summer-school activities over the months from June to September on a more regular basis, and, with the warmer temperature conditions and heat waves occurring in the spring–summer season, frequent indoor thermal discomfort is experienced, with negative impacts on occupants’ task and learning performance. Consequently, the need to guarantee adequate indoor environmental conditions in schools in the warm season is becoming of primary importance for local public authorities.
In the last decades, many research efforts have focused on educational buildings, exploring a wide variety of aspects from energy performance to indoor environmental quality (IEQ). Several works, specifically in the Italian context, addressed the topics of energy retrofit and of efficient energy management, mainly in the heating season [1,2,3,4], underlining that substantial energy savings of around 15% may be obtained with optimal energy system operation, as noted by Semprini et al. [2]. Some studies, such as a recent one by Nikolic’ et al. [5], also focused on the influence of occupants’ behavior on buildings’ HVAC energy consumption; by studying kindergartens in Serbia, the authors demonstrated how conventional occupancy patterns, derived according to standards and regulations, can significantly reduce the representativeness of buildings’ energy performance results, especially in the case of frequent variations in people occupancy. Others analyzed the indoor thermal conditions in school buildings by means of monitoring activities and questionnaires, such as Wang et al. [6] and de la Hoz-Torres et al. [7]. They highlighted the importance of accounting for indoor thermal conditions and occupants’ comfort perception in the building energy performance optimization process to guarantee adequate indoor thermal comfort and occupants’ task performance levels. Specifically, an interesting point made by Wang et al. [6] is that students are more tolerant to temperatures deviating from the neutral thermal sensation level in naturally ventilated classrooms than in heated or cooled indoor environments.
Among the studies addressing the energy performance of educational buildings in the cooling season, notably, Ascione et al. [8], Zafaranchi et al. [9], Liu et al. [10], and Aloshan et al. [11] focused on the building envelope design and retrofit solutions as means to enhance buildings’ cooling energy performance. Alwetaishi et al. [12] underlined the importance of an appropriate design for school buildings that is based on the local microclimate conditions for energy savings purposes and to guarantee adequate thermal comfort levels. Other researchers focused on the potential of ventilation strategies for energy performance optimization in the warm seasons [13,14,15]. Notably, Simonetti et al. [13] and Wang et al. [14] showed the potential of night ventilation to optimize the building cooling load. In detail, Wang et al. [14] optimized the energy performance of a Passive House school in Munich, Germany, highlighting the potential of night ventilation to reduce cooling energy consumption and enhance indoor thermal comfort. Similar conclusions were drawn by Alonso et al. in their study on ventilative cooling in highly insulated buildings [15]: indeed, by analyzing a case study of a kindergarten in Norway, they show the effectiveness of a mixed-mode ventilation system and night ventilation, which leverage lower outdoor air temperatures, in reducing the cooling energy load without compromising indoor air quality and thermal comfort. On the other hand, Grassie et al. [16], focusing on the English educational building stock, cast light on the limits of passive cooling measures and the need for mechanically driven cooling in case of hot weather conditions. A similar argument was made by Aguilar-Carrasco et al. [17], who noted that, despite the benefits brought by higher ventilation rates, additional strategies, such as active ventilation systems, are needed in case of overheating.
In this context, to the authors’ knowledge, few studies have addressed the need to enhance the indoor thermal conditions of educational buildings in the cooling season, specifically in the Italian context, to enable their use in the warmest months while ensuring adequate indoor thermal comfort levels. Indeed, many assume schools to be closed and do not effectively tackle the problem.
Given these premises, this work analyzes solutions and strategies to improve the indoor thermal environment and energy performance of school buildings in the north of Italy in the spring–summer months, spanning from passive to active measures selected among the most conventional ones, with the final goal of guaranteeing adequate thermal comfort and schoolwork performance levels while ensuring efficient cooling and ventilation system performance.
This manuscript is structured as follows. First, the methodology implemented to conduct the study has been reported in “Section 2”: after a brief description of the case study buildings’ main features and the geographical context, the energy models have been presented, and then data about the buildings’ energy performance and thermal comfort analysis have been detailed. Specifically, the analysis scenarios, the national and international standards, and the literature models used as references have been thoroughly described. On the other hand, “Section 3” is divided into two parts: the first one, “Section 3.1”, presents the outcomes of the passive cooling measures implemented, while the second part, “Section 3.2”, is dedicated to the implementation of the semi-passive and active strategies. Finally, in “Section 4”, the conclusions are drawn, and future developments of this research work are laid out.

2. Materials and Methods

2.1. Case Study Buildings and Geographical Context

This study focuses on two educational buildings in the city of Bolzano, which is located in the South Tyrol region in the north of Italy (geographical coordinates: 46°29′53.21″ N 11°21′17.21″ E) at around 262 m above sea level. Bolzano is characterized by a semi-continental climate with cold winters, hot summers, and quite large daily temperature excursions (Heating Degree Days with an 18 °C base temperature HDD18 = 1969 K·d and Cooling Degree Days with an 18 °C base temperature CDD18 = 605 K·d, both calculated according to the typical meteorological year weather data for Bolzano [18]).
The two case study school buildings considered in this analysis are a relatively dated kindergarten (defined as A) and a recently constructed primary school (defined as B). The first one (Kindergarten A) is representative of partially renovated dated constructions, while the second one (Primary School B) represents new, high-performance ones (Figure 1 and Figure 2). Both buildings are provided with a heating system only, lack cooling and mechanical ventilation, and rely on natural ventilation via manually opening windows. The main data of the buildings are reported in Table 1.
Kindergarten A is characterized by masonry and reinforced concrete walls (average thermal transmittance Uav-walls higher than 0.30 W·m−2·K−1) and a recently renovated green roof and triple-glazed windows (Uav-windows > 1.90 W·m−2·K−1). On the other hand, Primary School B has well-insulated masonry walls (Uav-walls = 0.26 W·m−2·K−1), a roof made of an insulated reinforced concrete system and a green roof system (Uav-roof = 0.10 W·m−2·K−1), and low-e triple-glazed units (Uav-windows = 1.25 W·m−2·K−1).
The building hosting Kindergarten A has an almost square shape, with one floor above ground and a basement. Specifically, Kindergarten A is located on the ground floor, while the underground does not belong to it and is not part of this analysis. In detail, the kindergarten layout is structured around a double-height central atrium with a gabled roof, which is surrounded by the administration office; the entrance; the “service” zone, hosting the kitchen, the storage, and the personnel’s changing rooms; and six “sections” blocks, with each block comprising a classroom, an adjacent “lunchroom”, and a restroom area. The six restroom areas present a double-height part with a gabled roof as well. External roller shades protect the glazed surfaces, except for the atrium ones and the restrooms’ upper windows.
Primary School B is a complex U-shaped building with the shortest side facing northeast, three floors above the ground, and a basement. On the northeast side, the school is connected to the public library, a two-story building extending toward the northeast, which is not included in the analysis. As for the school layout, the ground floor hosts the entrance area with a double-height hall located in the northeast branch, the canteen with the utility room located in the southeast branch, and the auditorium on the northwest side. Classrooms are located on the first and second floors and have different sun exposures on the northeast, southeast, and northwest sides. The underground floor hosts the kitchen, utility rooms, storage area, personnel changing rooms, and technical rooms, as well as the gym, a double-height semi-independent space connected to the U-shaped building and extending in the southeast direction. All windows are provided with external roller blinds.

2.2. Energy Models

The buildings’ energy models were created with EnergyPlus via Rhinoceros3D combined with Grasshopper and Honeybee plugins. Specifically, EnergyPlus version 22.2.0 Rhinoceros3D version 7, Grasshopper Build 1.0.0007 and Honeybee version 1.7.0 were used. People, lighting, and appliances were set according to international standards [21,22,23], the literature [24], and information provided by the schools’ administrations for both the school and summer-school months. Specifically, the occupancy and time schedules for the school months were set on the basis of the schools’ administration data, while, for the summer-school months, they were set in line with the ones of the “regular” school months and adjusted to reproduce the reasonable occupation patterns of the two buildings for indoor summer activities. Specifically, in both schools, classrooms’ occupancy hours were set as 8:00 am to 4:00 pm during the regular school months (i.e., from the 5th of September to the 9th of June) and 8:00 am to 5:00 pm during the summer-school months (i.e., from the 10th of June to the 4th of September). Indoor temperature data, collected during monitoring campaigns conducted in the kindergarten and the primary school in winter 2023 and winter 2019, respectively, were used for the calibration and validation of the two schools’ energy models [25,26]. For the monitoring of the indoor environment, dedicated sensors were used, namely, HOBO Carbon Dioxide/Temp/RH Data Loggers and HOBO Temperature/Relative Humidity/2 External Channel Data Loggers, which were set in the main representative classrooms of the two schools with a recording timestep of 10 min.

2.3. Energy Performance, Thermal Comfort Analysis, and Learning Performance

The cooling energy performance and thermal comfort analysis of the two schools was conducted considering the spring and summer months from the 15th of April to the 14th of October, i.e., the months not belonging to the conventional local heating season defined by the Italian government for Bolzano’s region [27], which is set as the 15th of April to the 14th of October. Furthermore, in the analysis, it was assumed that the two buildings remained open after the end of the “regular” school year to host summer-school camps with indoor activities for children.
A set of classrooms representative of the indoor thermal environment conditions in each school was considered for the analysis. For the kindergarten, Classrooms A1 and A2, with northwest and southeast sun exposure, respectively, and both with a net floor area of 46 m2, were selected. Specifically, Classroom A1 represents the most common indoor thermal environment conditions in the kindergarten, while A2, due to its orientation, is representative of the warmest indoor thermal environment. Both Classrooms A1 and A2 have a window-to-wall ratio of 0.34. As for the primary school, three zones representative of the indoor thermal environment in the classrooms’ areas were selected and identified as B1, B2, and B3, with about 487.5 m2, 485.4 m2, and 121 m2 net floor area, respectively. In detail, B1 is located on the first floor, corresponding to the southeast “branch” of the U-shaped building, and has almost 5 modular classrooms located on the southeast side, with windows facing southeast, and it is accessible via a corridor having windows oriented northwest. On the other hand, Zones B2 and B3 are located on the second floor: B2 corresponds to the northwest “branch” of the building, where 5 modular classrooms are located along the northwest side, having northwest solar exposure, and they are accessible via a corridor with windows facing southeast; Zone B3 is located on the short side of the “U”, with northeast solar exposure. Zones B1 and B2 have a window-to-wall ratio of 0.23, while Zone B3’s ratio is 0.38.
Different scenarios were defined to analyze the selected passive, semi-passive, and active strategies. Simulations started with the baseline Scenario 0, in which no shading system was implemented, and daytime natural ventilation rates and schedules were set to reproduce the regular windows’ manual opening pattern in the two schools. First, two passive strategies, i.e., shading system operation and daytime natural ventilation via manual operation of windows, were analyzed separately in Scenario 1 and Scenario 2, respectively, and then combined in Scenario 3 (Table 2). Afterward, the analysis of a semi-passive strategy (night free cooling (NFC) via mechanical ventilation system), applied to the most effective combination of the passive ones, was performed in Scenario 4. In Scenario 5, a decentralized air conditioning (AC) system was implemented and applied to the optimized building configurations of Scenario 4, the shading systems and NFC strategies were maintained, and daytime natural ventilation was substituted with mechanical ventilation. Finally, the same AC system was applied to the baseline scenario, resulting in Scenario 0 AC.
In the shading-control scenarios (from 1.1 to 1.4), daytime natural ventilation was set as in the baseline, while shading device operation was set based on the incident solar radiation on windows. Different shading-control setpoints were defined for each scenario, and the control logic was set so that, if the global solar irradiance incident on windows was higher than the setpoint, the shading system was deployed: (1.1) 140 W/m2, (1.2) 160 W/m2, (1.3) 180 W/m2, and (1.4) 200 W/m2.
In the daytime natural ventilation scenarios (from 2.1 to 2.4), no shading system was implemented, while for daytime natural ventilation via window opening, different airflow rates for the school and summer-school months were defined in each scenario as reported in Table 2. Furthermore, different ventilation schedules were implemented for the conventional school and the summer-school months: specifically, during the conventional school months, the windows were set to open every 2 h from 9:00 am to 4:00 pm from the 15th of April to the 9th of June and from the 5th of September to the 14th of October; during the summer-school months, the windows were opened every hour from 8:00 am to 6:00 pm from the 10th of June to the 4th of September; and during weekends and holidays, no ventilation was implemented.
The scenarios from 3.1.1 to 3.4.4 combine scenario strategy (1) related to shading controls and scenario strategy (2) related to daytime natural ventilation, and, based on the analysis results, the scenario with the most effective combination of the passive strategies was selected. Thus, in Scenario 4, night free cooling (NFC) was applied to the best-performing scenario strategy “3” via a decentralized mechanical ventilation system using fan coil units (FCUs) (Table 3). The FCU type with a maximum airflow of 1293 m3/h and a maximum total cooling capacity of 5880 W was selected. However, for NFC, the system was used to provide fresh outdoor air only; no air conditioning was applied. The choice to provide NFC via mechanical system was made to ensure the needed outdoor air-change rates in the indoor spaces during the early morning hours when schools are closed. Furthermore, both for security reasons and given the constraints of opening windows, it would be difficult to guarantee them otherwise. NFC was implemented in both buildings on school and summer-school days only for 3 h per day from 5:00 am to 8:00 am from May to September. (Only in the entrance area of Kindergarten A, NFC was also implemented in the months of April and October.) In the kindergarten, FCUs providing a total outdoor airflow rate of 849 m3/h were set in classrooms (which corresponds to almost 6.05 ACH), in the connected “lunch” rooms, and in the restrooms, entrance area, and administration office; two FCUs providing the same fresh airflow rate were set in the service area; and two FCUs providing 1293 m3/h were set in the atrium; resulting in a total NFC airflow rate of 21,298 m3/h, i.e., 3.75 ACH, in the whole school. In the primary school, a total of 9 FCUs providing 849 m3/h airflow rate were implemented in the major classroom areas located along the southeast and northwest “branches” of the building (such as B1 and B2), 2 FCUs providing 849 m3/h airflow rate were implemented in the classroom areas with smaller dimensions and located on the northeast side of the building (such as B3), a total of 4 FCUs providing 1293 m3/h were implemented in the hallway, and 2 FCUs providing 1293 m3/h were implemented in the canteen, gym, and auditorium. Thus, the total NFC airflow rate applied in Primary School B was equal to 34,809 m3/h, i.e., 2.38 ACH.
In Scenario 5, the same decentralized system with ducted fan coil units (FCUs) implemented for NFC was assumed to provide both active cooling and mechanical ventilation in both schools (Table 4 and Table 5). Specifically, the FCU model with a maximum cooling airflow of 1293 m3/h and a maximum total cooling capacity of 5880 W was selected to be able to cover the buildings’ peak loads and satisfy the required outdoor airflow rates [22,28]. In both schools, the cooling setpoint temperature was set to 26 °C, and the daily natural ventilation via manual operation of windows was substituted with mechanical ventilation while maintaining NFC. In detail, in Kindergarten A, 1 FCU was set to be active in each classroom, “lunch” room, restroom, in the entrance area, and in the administration office; two FCUs in the service area; and four FCUs in the atrium. Thus, the FCUs’ total installed cooling power and maximum supply airflow rate for cooling and mechanical ventilation in the kindergarten were set to about 153 kW and 33,696 m3/h, respectively. In Primary School B, as defined for the NFC scenario, 9 FCUs were activated in the classroom areas located in the southeast and northwest sections of the building; 2 FCUs in the classroom zones on the northeast side; a total of 6 FCUs in the hallway, gym, and auditorium; and 4 FCUs in the canteen and the basement. As a result, the FCUs’ total installed cooling power and maximum supply airflow rate for cooling and mechanical ventilation in the primary school amounted to 335 kW and 73,701 m3/h, respectively.
Finally, in Scenario 0 AC, the same type of AC system as the one in Scenario 5 (i.e., decentralized with ducted FCUs) was implemented in the baseline building configurations, substituting daytime natural ventilation via the operation of windows with mechanical ventilation, in order to evaluate the total seasonal power consumption for cooling and mechanical ventilation in absence of the optimization of passive and semi-passive strategies. The main features of the heat pumps implemented in the two buildings in Scenarios 5 and 0 AC are reported in Table 5. The energy consumption results of Scenario 5 were compared with the ones of Scenario 0 AC to evaluate the energy savings for cooling and mechanical ventilation, which could be achieved thanks to the enhancement of the buildings’ energy performance via passive and semi-passive strategies. Then, the electricity consumption for both NCF and cooling system operation in Scenario 5 and for the cooling system operation only in Scenario 0 AC was evaluated in both schools. The average electricity price (in €/kWh) for non-household consumers, registered in Italy in the second semester of 2024, was retrieved from Eurostat database [29] and used for the assessment, i.e., 0.3129 €/kWh.
The thermal comfort analysis was conducted for the representative classrooms based on the technical standard EN 16798-1:2019 [28]. Specifically, different metrics were considered depending on the analyzed scenario: the mean hourly indoor temperature distribution; the monthly mean temperatures; the seasonal mean, peak, and minimum temperatures; and the temperature cumulative curves; as well as the Predicted Mean Vote (PMV) and Predicted Percentage Dissatisfied (PPD) indexes.
As for the children’s learning performance analysis as a function of the indoor air temperature, schoolwork relative performance according to Wargocki et al.’s model [30] was assessed and analyzed in detail for the selected classrooms in Scenarios 0, 3.1.1, 4, and 5. The schoolwork relative performance model equation, describing the relationship between relative performance (“y”), expressed as percentage, and air temperature (“t”), in degrees Celsius (°C), has been reported below:
y = 0.2269t2 − 13.441t + 277.84

3. Results

3.1. Passive Cooling Strategies

The analysis has shown the extent of the passive cooling strategies’ effectiveness in enhancing the indoor thermal comfort in free-floating conditions in the two buildings and the limit beyond which active strategies are needed. Specifically, by analyzing the passive strategies based on shading controls and increased natural ventilation, first separately (Scenarios 1 and 2) and then combined (Scenario 3), with respect to the baseline Scenario 0, it was possible to appreciate the efficacy of each one in improving the indoor thermal environment and the effects of their interaction.
Overall, similar behaviors were observed in both schools, with a higher risk of overheating in Kindergarten A with respect to Primary School B. As can be observed in Figure 3 and Figure 4, starting from the baseline, higher indoor average temperatures were simulated in the analyzed classrooms of the kindergarten compared to those of the recently constructed primary school, with average values between 30.54 °C and 31.23 °C in Classrooms A1 and A2 and between 27.5 °C and 28 °C in Classrooms B1, B2, and B3.
The implementation of the shading-control strategies led to a significant enhancement of the indoor thermal environment in both buildings. The lower and more restrictive the shading setpoint, the higher the temperature drop: indeed, a shading setpoint of 140 W/m2 enabled the screening of most of the solar radiation in the warmest hours of the day. In both schools, the shading-control strategies facilitated a significant decrease in the indoor temperature of almost 12% in Kindergarten A, where the average temperatures reached almost 27 °C, and 6% in B, where they oscillated between 25.7 °C and 26.4 °C.
As for the ventilation strategies, they were less effective in limiting the indoor temperature levels than the shading ones, with temperature drops of around 6% and 5% in Kindergarten A and Primary School B, respectively. Indeed, in Scenarios 2.1 to 2.4, the average temperatures ranged between 28 °C and 30 °C in the kindergarten and fell between 25.7 °C and 28 °C in the primary school. The higher the increase in the ventilation rate, the higher the temperature drop in both schools.
On the other hand, taking into account the combination of shading and ventilation strategies (please see Figure 5, Figure 6, Figure 7 and Figure 8), by combining the most restrictive shading setpoint with the lowest ventilation rates, despite the indoor average temperatures being slightly higher than the ones of the scenarios with higher ventilation rates of almost 0.7 °C and 0.5 °C in A and B, respectively, it was possible to limit the indoor temperature peaks to the greatest extent in both buildings. Thus, Scenario 3.1.1, with a 140 W/m2 shading system setpoint and limited natural ventilation rates of 2.5 and 5 ACH applied during school and summer-school ventilation schedules, respectively (as described in Table 2), was selected as the most effective combination of passive strategies among the scenarios analyzed.
Overall, considering that in Scenario 0, the percentage of occupied hours with indoor operative temperature below 28 °C was limited to around 19% and 13% in the analyzed classrooms of Kindergarten A, while it was about 51% and 46% in Primary School B, the implementation of the passive cooling strategies of Scenario 3.1.1 was more effective in reducing the indoor temperature levels in the kindergarten compared to the primary school (Figure 9 and Figure 10). Indeed, the increase in the percentage of occupied hours falling below 28 °C reached 55–57% in the case study classrooms of A, while it ranged between 37% and 41% in B1, B2, and B3. On the other hand, considering the 26 °C highest limit of thermal comfort category II [28], in Scenario 3.1.1, a higher increase in the percentage of occupied hours below or equal to that threshold, with respect to the baseline, was observed in Primary School B, as can be observed from the steepness of the temperature curves in Figure 9 and Figure 10.

3.2. Night Free Cooling and AC System

In Scenario 4, with the implementation of the night free cooling strategy in the optimized building configuration of Scenario 3.1.1 (i.e., the scenario combining the most restrictive shading system setpoint of 140 W/m2 with limited natural ventilation rates of 2.5 and 5 ACH applied during school and summer-school ventilation schedules, respectively, as reported in Table 2), it was possible to further reduce the indoor average temperatures with limited electricity consumption, especially in the spring months of May and June and in the month of September (as can be observed in Table 6, Table 7 and Table 8). The decrease in the indoor temperatures with respect to Scenario 3.1.1 resulted in a monthly average temperature difference ranging between almost 1 °C and 1.6 °C. Comparing the two schools, and considering the observations previously made about the efficacy of the passive strategies in the two buildings, the NFC strategy turned out to be more effective in the kindergarten than in the primary school in improving the indoor thermal comfort: indeed, the increase in the percentage of occupied hours below 26 °C, compared to Scenario 3.1.1, was almost 30% in the kindergarten and 13% in the primary school. Nonetheless, the combination of both passive strategies and NFC in Scenario 4 led to a significant enhancement of the indoor thermal environment in both schools, with the percentage of occupied hours with an indoor operative temperature below or equal to 26 °C being 69% and 68% in Classrooms A1 and A2, respectively, and reaching 74% in Zones B1 and B2 and 69% in B3.
Given the limits of the passive and semi-passive cooling strategies in reducing the indoor temperature peaks and guaranteeing adequate indoor thermal comfort conditions over the whole building occupancy period, the use of an active cooling system turned out to be necessary in both schools. Thus, a decentralized AC system with ducted fan coil units was evaluated and implemented in the two buildings in Scenario 5 (i.e., the scenario combining the optimized building configurations of Scenario 4 with the AC system and replacing daytime natural ventilation via window opening with mechanical ventilation while maintaining NFC). The system choice was made to allow independent control of each zone and guarantee the required outdoor air changes for the sake of the indoor air quality [28]. Overall, in both schools, a similar sensible cooling energy consumption trend was observed over the whole cooling season, with the highest monthly sensible cooling energy consumption of the FCUs recorded in the month of August. Comparing the two schools, the seasonal sensible cooling energy consumption per meter squared was higher in the kindergarten than in the primary school, with 5.63 kWh/m2 and 3.30 kWh/m2 in the two schools, respectively.
Considering Scenarios 5 and 0 AC (i.e., the scenario where the same type of AC system as in Scenario 5 was implemented in the baseline building configurations, substituting daytime natural ventilation via window opening with mechanical ventilation), the sensible cooling energy consumption obtained in 5 was about 60% and 30% of that obtained in 0 AC in Kindergarten A and Primary School B, respectively. Therefore, in both schools, it was possible to cover the building’s cooling energy need with limited total seasonal cooling power consumption of the heat pump, which, in the kindergarten, achieved about 1.34 kWh/m2, i.e., almost 63% of the 2.13 kWh/m2 of Scenario 0 AC, while in the primary school, it was equal to 0.67 kWh/m2, i.e., about 31% of the 2.16 kWh/m2 of Scenario 0 AC (Table 9). Furthermore, the electricity consumption for the operation of daytime mechanical ventilation was extremely limited, i.e., about 0.103 kWh/m2 and 0.149 kWh/m2 in schools A and B, respectively. The results obtained underline the importance of building performance optimization through passive cooling strategies to significantly enhance the indoor thermal environment and reduce the need for active cooling. In terms of electricity costs for the AC system’s operation and for NFC (Table 10), the total seasonal specific cost was 0.46 €/m2 for the kindergarten and 0.28 €/m2 for the primary school.
In terms of indoor thermal comfort, the AC system enabled the maintenance of good levels in both schools, as shown in Figure 11. Indeed, in the months from June to September, in the two schools, the average PMV values were within thermal comfort category I and close to the neutral thermal comfort condition. In detail, in the kindergarten, the average PMV was almost 0.26 and 0.27 in the two classrooms A1 and A2, respectively, and the PPD index average values were around 10%, while the PPD peaks were limited, remaining below 26.5%. As for the primary school, similar results were obtained, and, specifically, the average PMV was around 0.17 in Classrooms B1 and B2 and 0.22 in B3, and the average PPD index was around 11% in all three case study classrooms, with slightly higher peaks compared to the kindergarten, reaching almost 31.3%, 30.6%, and 27.9% in the three classrooms, respectively.
As can be observed in Figure 12, the enhancement of the indoor thermal environment, linked to the implementation of the AC system in Scenario 5, led to an enhancement of students’ learning performance in both schools with respect to the scenarios with only passive and semi-passive cooling strategies. Specifically, in Scenarios 0 and 3.1.1, the average schoolwork relative performance, as a function of the indoor temperature, was respectively 79% and 81% in the case study classrooms of Kindergarten A and almost 79% and 82%, respectively, in all analyzed classrooms of Primary School B. In Scenario 4, it was about 84% in the kindergarten and between 83% and 84% in the primary school, while in all three scenarios, the lowest performance levels reached almost 79% in all the case study classrooms of both schools. On the contrary, with the implementation of the AC system, the average levels of schoolwork relative performance increased, reaching about 86% in the analyzed classrooms of both schools, with the lowest performance levels never falling below 81%.

4. Conclusions

The present study focused on the analysis of a set of passive, semi-passive, and active cooling strategies with the aim of improving indoor thermal comfort in two case study public school buildings in the city of Bolzano, Italy, in the spring and summer months. First, passive cooling strategies, i.e., shading systems and daytime natural ventilation control measures, were assessed separately and then combined. Afterward, night free cooling via a mechanical ventilation system was applied, and, finally, an AC system with mechanical ventilation was implemented. The analysis was carried out with the use of EnergyPlus simulation software.
This study highlighted the efficacy of passive and semi-passive strategies in enhancing the indoor thermal environment in the cooling season and the limit beyond which the use of a cooling system with mechanical ventilation is required to guarantee adequate levels of indoor thermal comfort and occupants’ task performance.
Specifically, the following main considerations could be drawn from this work:
-
Having well-designed shading devices, in terms of system and operation, is of primary importance, as they play a crucial role in maintaining adequate indoor thermal environment conditions, especially in the warm seasons, in both dated and recently constructed buildings. Indeed, protecting from solar radiation in the warmest hours of the day, they allowed a reduction in the average indoor temperature of over 3 °C in the warmest months for the considered case studies.
-
Daytime natural ventilation proved less effective than shading system operation measures in enhancing indoor thermal comfort.
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In terms of combining passive strategies, the most restrictive shading-control setpoint together with limited daytime natural ventilation rates proved to be the best-performing one (Scenario 3.1.1) in both schools. Indeed, it allowed a significant enhancement of the indoor thermal environment with respect to the baseline, leading to the lowest temperature peaks among the passive strategy scenarios analyzed and to the seasonal average values of the mean hourly temperatures falling within comfort category III in the kindergarten and I in the primary school. Furthermore, the percentage of schooltime hours falling below the higher limit of comfort category II (i.e., 26 °C) in the case study classrooms of the two schools reached about 38% in the analyzed classrooms of Kindergarten A (almost 29% more than in the baseline) and about 60% in the ones of Primary School B (almost 35% more than in Scenario 0).
-
As for the implementation of the night free cooling strategy via mechanical ventilation, the results obtained show the great potential of this measure in enhancing the indoor thermal environment. Indeed, in Scenario 4, the percentage of schooltime hours falling below 26 °C reached almost 68% and 73% in the analyzed classrooms of Kindergarten A and Primary School B, respectively, with a limited total electricity consumption for the FCU operation amounting to 0.04 kWh/m2 in the kindergarten and 0.09 kWh/m2 in the primary school.
-
Given the limits of the passive and semi-passive cooling strategies in guaranteeing adequate indoor thermal comfort levels over the entire occupation time in both school buildings, the use of an AC system with mechanical ventilation turns out to be necessary.
To conclude, a preliminary enhancement of the building performance through simple, well-designed strategies for shading system operation and night free cooling via mechanical ventilation allows a substantial reduction in the cooling energy consumption compared to the use of the AC system in a non-optimized building, as in Scenario 0 AC. Furthermore, given the limited electricity consumption for the AC system and mechanical ventilation operation and their benefits in terms of allowing the use of the buildings for indoor activities over the entire cooling season while maintaining adequate indoor thermal comfort in the warmest months, these retrofit initiatives may be worth considering for the local public administration. The moderate energy consumption also suggests that, in the case of warmer temperature conditions, the total electricity costs for the AC and mechanical ventilation systems would remain affordable, and the benefits brought by the systems would still outweigh the costs.
Based on the outcomes of this work, future research efforts will be dedicated to the study of more advanced solutions for an efficient AC system and mechanical ventilation operation based on occupancy level that are able to automatically switch between active and free cooling operation modes over daytime hours. Last but not least, it is recommended to extend the analysis to include the study of the indoor daylighting to define effective shading system operation strategies based on both solar radiation and indoor daylighting conditions (such as illuminance levels and glare) to guarantee both thermal and visual comfort. Artificial lighting control will be implemented as well, based on the indoor illuminance levels, to maximize the efficiency of the buildings’ operation. Although the outcomes of this work are specific to the case studies analyzed, they may be regarded as general guidelines for identifying the main issues and limitations in the efforts to provide adequate indoor thermal environment conditions in school buildings during the warm season and defining suitable solutions to effectively tackle the problem in other buildings.

Author Contributions

Conceptualization, A.E.H.; methodology, A.E.H.; validation, A.E.H.; formal analysis, A.E.H.; investigation, A.E.H.; resources, G.P. and A.G.; data curation, A.E.H.; writing—original draft preparation, A.E.H.; writing—review and editing, A.E.H., G.P., and A.G.; visualization, A.E.H.; supervision, G.P. and A.G.; project administration, G.P. and A.G.; funding acquisition, G.P. and A.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research has been funded by the European Union-Next Generation EU, Mission 4 Component 1 CUP I52B22000790005 and it has been developed within the framework of the PhD Research Scholarship “Support to the public administration for developing new energy and sustainable policies for the built environment” according to Italian ministerial decree D.M. 351/2022.

Data Availability Statement

Data will be made available on request.

Acknowledgments

This study has been developed with the support of the Office of Geology, Civil Protection and Energy of the Municipality of Bozen-Bolzano.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. East view of Kindergarten A main façade (left) [19] and northeast view of the main façade of Primary School B (right) [20].
Figure 1. East view of Kindergarten A main façade (left) [19] and northeast view of the main façade of Primary School B (right) [20].
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Figure 2. Southeast and east views of the Kindergarten A and Primary School B energy models, respectively (including the underground floors).
Figure 2. Southeast and east views of the Kindergarten A and Primary School B energy models, respectively (including the underground floors).
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Figure 3. Indoor temperature distribution in the two analyzed classrooms of the kindergarten, A1 and A2, after the implementation of the shading-control (left) and natural ventilation (right) strategies, evaluated with respect to the baseline scenario (0) and having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
Figure 3. Indoor temperature distribution in the two analyzed classrooms of the kindergarten, A1 and A2, after the implementation of the shading-control (left) and natural ventilation (right) strategies, evaluated with respect to the baseline scenario (0) and having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
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Figure 4. Indoor temperature distribution in the two analyzed classrooms of the primary school, B1 and B2, after the implementation of the shading-control (left) and the natural ventilation (right) strategies, evaluated with respect to the baseline scenario (0) and having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
Figure 4. Indoor temperature distribution in the two analyzed classrooms of the primary school, B1 and B2, after the implementation of the shading-control (left) and the natural ventilation (right) strategies, evaluated with respect to the baseline scenario (0) and having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
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Figure 5. Indoor temperature distribution in the two analyzed classrooms of the kindergarten, A1 and A2, after the implementation of the shading-control and natural ventilation strategies of Scenarios 3.1 (left) and 3.2 (right), evaluated by having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
Figure 5. Indoor temperature distribution in the two analyzed classrooms of the kindergarten, A1 and A2, after the implementation of the shading-control and natural ventilation strategies of Scenarios 3.1 (left) and 3.2 (right), evaluated by having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
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Figure 6. Indoor temperature distribution in the two analyzed classrooms of the kindergarten, A1 and A2, after the implementation of the shading-control and natural ventilation strategies of Scenarios 3.3 (left) and 3.4 (right), evaluated by having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
Figure 6. Indoor temperature distribution in the two analyzed classrooms of the kindergarten, A1 and A2, after the implementation of the shading-control and natural ventilation strategies of Scenarios 3.3 (left) and 3.4 (right), evaluated by having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
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Figure 7. Indoor temperature distribution in the two analyzed classrooms of the primary school, B1 and B2, after the implementation of the shading-control and natural ventilation strategies of Scenarios 3.1 (left) and 3.2 (right), evaluated by having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
Figure 7. Indoor temperature distribution in the two analyzed classrooms of the primary school, B1 and B2, after the implementation of the shading-control and natural ventilation strategies of Scenarios 3.1 (left) and 3.2 (right), evaluated by having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
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Figure 8. Indoor temperature distribution in the two analyzed classrooms of the primary school, B1 and B2, after the implementation of the shading-control and natural ventilation strategies of Scenarios 3.3 (left) and 3.4 (right), evaluated by having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
Figure 8. Indoor temperature distribution in the two analyzed classrooms of the primary school, B1 and B2, after the implementation of the shading-control and natural ventilation strategies of Scenarios 3.3 (left) and 3.4 (right), evaluated by having as reference the temperature upper limits of the thermal environment categories [28] over the occupied hours of the cooling season.
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Figure 9. Comparison of the temperature cumulative curves of the selected classrooms of the kindergarten, evaluated in Scenarios 0 (baseline), 3.1.1 (most effective passive strategy combination), and 4 (NFC applied to 3.1.1) with respect to the temperature upper limit thresholds of the thermal comfort categories of EN 16798-1:2019 [28].
Figure 9. Comparison of the temperature cumulative curves of the selected classrooms of the kindergarten, evaluated in Scenarios 0 (baseline), 3.1.1 (most effective passive strategy combination), and 4 (NFC applied to 3.1.1) with respect to the temperature upper limit thresholds of the thermal comfort categories of EN 16798-1:2019 [28].
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Figure 10. Comparison of the temperature cumulative curves of the selected classrooms of the primary school, evaluated in Scenarios 0 (baseline), 3.1.1 (most effective passive strategy combination), and 4 (NFC applied to 3.1.1) with respect to the temperature upper limit thresholds of the thermal comfort categories of EN 16798-1:2019 [28].
Figure 10. Comparison of the temperature cumulative curves of the selected classrooms of the primary school, evaluated in Scenarios 0 (baseline), 3.1.1 (most effective passive strategy combination), and 4 (NFC applied to 3.1.1) with respect to the temperature upper limit thresholds of the thermal comfort categories of EN 16798-1:2019 [28].
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Figure 11. Predicted Mean Vote index (PMV) (left) with respect to the PMV upper and lower limits of the thermal environment categories [28] and Predicted Percentage Dissatisfied index (PPD) (right) evaluated for the selected classrooms of the two schools, A and B, in Scenario 5, under the implementation of the AC system, considering the months from June to September.
Figure 11. Predicted Mean Vote index (PMV) (left) with respect to the PMV upper and lower limits of the thermal environment categories [28] and Predicted Percentage Dissatisfied index (PPD) (right) evaluated for the selected classrooms of the two schools, A and B, in Scenario 5, under the implementation of the AC system, considering the months from June to September.
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Figure 12. Schoolwork relative performance evaluated for the selected classrooms of the two schools, A (left) and B (right), in Scenarios 0, 3.1.1, 4, and 5, considering the months from June to September.
Figure 12. Schoolwork relative performance evaluated for the selected classrooms of the two schools, A (left) and B (right), in Scenarios 0, 3.1.1, 4, and 5, considering the months from June to September.
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Table 1. School buildings general data.
Table 1. School buildings general data.
SchoolConstruction PeriodNet Heated Surface Area [m2]Net Heated Volume [m3]Shape Factor—Envelope Surface-to-Volume Ratio [m−1]Window-to-Wall Ratio [-]
Kindergarten A1971123540320.400.30
Primary School B2014516515,8180.360.23
Table 2. Passive cooling strategy scenarios.
Table 2. Passive cooling strategy scenarios.
StrategyScenario CodeShading System Control Setpoint:
Incident Solar
Radiation on
Window [W/m2]		Natural Ventilation via Manual Operation of Windows
Rate [ACH]Schedule
Baseline0No Shading
(15 April–14 October)		2.5 15 2School (from 15 April to 9 June and from 5 September to 14 October): Every 2 h from 9 am to 4 pm.
Summer school (from 10 June to 4 September): Every 2 h from 9 am to 6 pm.
Weekends and holidays: Always off from 15 April to 14 October.
1—Shading Systems
Control		1.1140As BaselineAs Baseline
1.2160
1.3180
1.4200
2—Daytime Natural Ventilation2.1No Shading2.5 15 2School (from 15 April to 9 June and from 5 September to 14 October):
Every 2 h from 9 am to 4 pm.
Summer school (from 10 June to 4 September): Every hour from 8 am to 6 pm.
Weekends and holidays: Always off from 15 April to 14 October.
2.23 16 2
2.33.5 17 2
2.44 18 2
3—Shading and Natural VentilationFrom 3.1.1 to 3.1.4140Ventilation rates as in strategy 2 for each shading-control strategy
(2.5 1/5 2,
3 1/6 2,
3.5 1/7 2,
4 1/8 2)		School (from 15 April to 09/06 and from 5 September to 14 October):
Every 2 h from 9 am to 4 pm.
Summer school (from 10 June to 4 September): Every hour from 8 am to 6 pm.
Weekends and holidays: Always off from 15 April to 14 October.
From 3.2.1 to 3.2.4160
From 3.3.1 to 3.3.4180
From 3.4.1 to 3.4.4200
1 School: from 15/04 to 09/06 and from 05/09 to 14/10 included. 2 Summer school: from 10/06 to 04/09 included.
Table 3. Night free cooling strategy (Scenario 4).
Table 3. Night free cooling strategy (Scenario 4).
Scenario 4Shading System
Control Strategy		Daytime
Natural
Ventilation		Night Free Cooling via Mechanical Ventilation 1
Active FCUs per ZoneAirflow Rate per FCU—Outdoor Air Only [m3/h]Cooling and
Mechanical
Ventilation Schedule
N° FCUsZone
Kindergarten AAs in Scenario 3.1.1As in Scenario 3.1.11Classrooms, “Lunch” rooms, Restrooms849From 5 am to 8 am.
All zones except the Entrance: From May to September included.
Entrance area only: From April to October included.
2Service Area849
2Atrium1293
1Entrance Area, Administration Office849
Primary School BAs in Scenario 3.1.1As in Scenario 3.1.19Classroom Zone in the Southeast Section (i.e., B1);
2 Classroom Zones in the Northwest Section (i.e., B2 and an additional zone like B2 but located on 1st floor).		849From 5 am to 8 am.
All zones: From May to September included.
22 Classroom Zones in the Northeast Section (i.e., B3 and an additional zone like B3 but located on 1st floor)849
4Hallway1293
2Canteen, Gym, Auditorium1293
1 Mechanical ventilation implemented with FCUs and to provide fresh outdoor air only (no recirculation).
Table 4. AC and mechanical ventilation system strategy (Scenario 5).
Table 4. AC and mechanical ventilation system strategy (Scenario 5).
Scenario 5AC and Mechanical Ventilation System 1
Cooling
Temperature
Setpoint [°C]		Active FCUs per ZoneMaximum
Airflow Rate per FCU—Outdoor Air Only [m3/h]		Maximum Total Cooling Capacity per FCU [W]Cooling and
Mechanical
Ventilation Schedule
N° FCUsZone
Kindergarten A261Classrooms, “Lunch” rooms, Restrooms12935880School 2:
h. 8 am–4 pm.
Summer School 3: h. 8 am–5 pm
2Service AreaSchool 2 and Summer School 3: h. 10 am–2 pm
4AtriumSchool 2:
h. 8 am–4 pm.
Summer School 3: h. 8 am–5 pm
1Entrance Area, Administration OfficeSchool 2 and Summer School 3:
h. 8 am–4 pm
Primary School B269Classroom Zone in the Southeast Section (i.e., B1);
2 Classroom Zones in the Northwest Section (i.e., B2 and same zone as B2 but located on 1st floor)		12935880School 2:
h. 8 am–4 pm.
Summer School 3: h. 8 am–5 pm
22 Classroom Zones in the Northeast Section (i.e., B3 and same zone as B3 but located on 1st floor)12935880
6Hallway, Gym, Auditorium12935880
4Canteen, Basement12935880
1 Mechanical ventilation to substitute daytime natural ventilation via operation of windows and to provide outdoor air only (no recirculation). 2 School: from 15/04 to 09/06 and from 05/09 to 14/10 included. 3 Summer school: from 10/06 to 04/09 included.
Table 5. Heat pumps serving the AC and mechanical ventilation system for the two school buildings in Scenarios 0 AC and 5.
Table 5. Heat pumps serving the AC and mechanical ventilation system for the two school buildings in Scenarios 0 AC and 5.
Heat Pump DataOverall Cooling Capacity [kW]Overall Input Power [kW]Energy Efficiency Ratio—EERSeasonal Energy Efficiency Ratio—SEERSeasonal Space Cooling Energy Efficiency—ηs,c
0 AC50 AC50 AC50 AC50 AC5
Kindergarten A88.774.136.6252.934.44.21173165.4
Primary School B487.3183167.659.62.913.075.054.94199194.6
Table 6. Monthly mean indoor temperatures and seasonal average, peak, and minimum temperatures in the analyzed classrooms of the kindergarten in Scenarios 0 (baseline), 3.1.1 (most effective passive strategy combination), and 4 (NFC applied to 3.1.1), evaluated considering the schooltime hours only.
Table 6. Monthly mean indoor temperatures and seasonal average, peak, and minimum temperatures in the analyzed classrooms of the kindergarten in Scenarios 0 (baseline), 3.1.1 (most effective passive strategy combination), and 4 (NFC applied to 3.1.1), evaluated considering the schooltime hours only.
Scenarios 0, 3.1.1, and 4Kindergarten A:
Monthly Average Indoor Air Temperature in the Schooltime Hours Only [°C]
0-A13.1.1-A14-A10-A23.1.1-A24-A2
Apr25.4921.9321.9325.1822.0622.06
May30.3225.9823.1731.0026.2323.37
Jun31.1727.0925.3831.2527.1225.41
Jul32.2027.6526.4032.5827.7426.47
Aug32.1227.1325.7032.8727.2725.81
Sept31.1927.1024.2632.7727.3424.46
Oct24.9422.2721.5226.6622.4321.70
Seasonal Average Temperature [°C]30.5426.3024.5531.2326.4524.68
Seasonal Peak Temperature [°C]35.3132.1131.638.3532.1731.71
Seasonal Lowest Temperature [°C]22.7820.5718.5921.9120.7318.77
Table 7. Monthly mean indoor temperature and seasonal temperature means, peaks, and minimums in the analyzed classrooms of the primary school in Scenarios 0 (baseline), 3.1.1 (most effective passive strategy combination), and 4 (NFC applied to 3.1.1), evaluated considering the schooltime hours only.
Table 7. Monthly mean indoor temperature and seasonal temperature means, peaks, and minimums in the analyzed classrooms of the primary school in Scenarios 0 (baseline), 3.1.1 (most effective passive strategy combination), and 4 (NFC applied to 3.1.1), evaluated considering the schooltime hours only.
Scenarios 0, 3.1.1, and 4Primary School B:
Monthly Average Indoor Air Temperature in the Schooltime Hours Only [°C]
0-B13.1.1-B14-B10-B23.1.1-B24-B20-B33.1.1-B34-B3
Apr21.6620.9220.9221.7821.0421.0421.9420.9820.98
May25.1123.3022.3125.5323.5122.4525.7723.7122.84
Jun27.5925.4024.4728.1125.5624.5428.1225.8525.01
Jul29.2926.4925.8429.7626.5825.9029.7426.8626.27
Aug29.6226.3425.5429.9526.3625.5430.1726.6225.92
Sept28.9726.3824.8229.1226.4524.8329.5226.4525.12
Oct25.3023.2022.0125.3423.3122.0225.4222.7821.79
Seasonal Average
Temperature [°C]		27.5125.1124.1827.8425.2224.2428.0025.3524.55
Seasonal Peak
Temperature [°C]		32.0630.6630.0532.3630.7030.0632.5331.1030.56
Seasonal Lowest
Temperature [°C]		19.2518.9718.9719.3119.0519.0519.3718.9418.94
Table 8. Total monthly and seasonal sensible cooling energy consumption in Scenarios 0 AC and 5 and electricity consumption of the fan coil units for daytime mechanical ventilation and NFC operation in the two schools in Scenario 5.
Table 8. Total monthly and seasonal sensible cooling energy consumption in Scenarios 0 AC and 5 and electricity consumption of the fan coil units for daytime mechanical ventilation and NFC operation in the two schools in Scenario 5.
Scenarios 0-AC and 5Total Sensible Cooling Energy Consumption of the FCUs [Wh/m2]Total Electricity
Consumption of the FCUs for Daytime
Mechanical Ventilation [Wh/m2]		Total Electricity
Consumption of the FCUs for NFC Operation [Wh/m2]
MonthlyA-0 ACA-5B-0 ACB-5A-5B-5A-5B-5
Apr1.700.00006.8728.820.110
May550.6681.47369.0337.1516.8028.677.5418.58
Jun2741.601798.963398.131007.8417.0926.887.2017.73
Jul2303.141526.902624.41862.1918.8528.107.2017.73
Aug2923.151810.333650.651165.4219.3123.797.5418.58
Sep867.24409.27858.15231.0316.2512.487.2017.73
Oct0.000.00007.6428.820.130
Total Seasonal [kWh/m2]9.395.6310.903.300.1030.1490.040.09
Total Seasonal Peak [kW]86,81870,635469,859178,436----
Table 9. Heat pump seasonal power consumption for the two schools in Scenarios 0 AC and 5.
Table 9. Heat pump seasonal power consumption for the two schools in Scenarios 0 AC and 5.
SchoolHeat Pump Seasonal
Cooling Power
Consumption [kWh]		Heat Pump Specific Seasonal Cooling Power
Consumption [kWh/m2]		Ratio of Heat Pump Cooling Power Consumption in
Scenarios 5 and 0 AC [-]
0 AC50 AC5
Kindergarten A2891.921811.672.131.3463%
Primary School B9427.332920.812.160.6731%
Table 10. Total seasonal electricity cost for heat pump cooling power consumption, daytime mechanical ventilation, and NFC operation in Scenarios 0 AC and 5.
Table 10. Total seasonal electricity cost for heat pump cooling power consumption, daytime mechanical ventilation, and NFC operation in Scenarios 0 AC and 5.
SchoolTotal Seasonal Electricity Cost for Heat Pump Cooling Power Consumption, Daytime Mechanical Ventilation, and NFC Operation [€]Total Seasonal Specific Electricity Cost for Heat Pump Cooling Power Consumption, Daytime Mechanical Ventilation, and NFC Operation [€/m2]
0 AC50 AC5
Kindergarten A904.88626.130.670.46
Primary School B2949.811240.650.680.28
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El Hokayem, A.; Pernigotto, G.; Gasparella, A. Enhancement of Thermal Comfort and Energy Performance of Educational Buildings in the Warm Season: The Case Study of Two Public Schools in Bolzano, Italy. Energies 2025, 18, 4483. https://doi.org/10.3390/en18174483

AMA Style

El Hokayem A, Pernigotto G, Gasparella A. Enhancement of Thermal Comfort and Energy Performance of Educational Buildings in the Warm Season: The Case Study of Two Public Schools in Bolzano, Italy. Energies. 2025; 18(17):4483. https://doi.org/10.3390/en18174483

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El Hokayem, Angelica, Giovanni Pernigotto, and Andrea Gasparella. 2025. "Enhancement of Thermal Comfort and Energy Performance of Educational Buildings in the Warm Season: The Case Study of Two Public Schools in Bolzano, Italy" Energies 18, no. 17: 4483. https://doi.org/10.3390/en18174483

APA Style

El Hokayem, A., Pernigotto, G., & Gasparella, A. (2025). Enhancement of Thermal Comfort and Energy Performance of Educational Buildings in the Warm Season: The Case Study of Two Public Schools in Bolzano, Italy. Energies, 18(17), 4483. https://doi.org/10.3390/en18174483

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