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In this work, we propose to extend an efficient strategy for robust optimization when a large number of uncertainties is considered, in order to include multi-criteria decision making tools. This strategy is based on ANOVA analysis for reducing the stochastic dimension and a massive use of metamodels for predicting the sensitivity indexes in the design variables plan. This approach is applied to the optimization under uncertainty of horizontal ground heat exchangers, used in Ground Source Heat Pumps (GSHPs) for heating and cooling of buildings. System efficiency is maximized taking into account several uncertain parameters, such as the heat conductivity of the ground around the tubes, the velocity inside the tubes and the depth of installation.

International audience; Covariance decomposition of output variance is used in this paper to take account of interactions between non-orthogonal components in anchored ANOVA method. Results show this approach is less sensitive to the anchor reference point than existing method. Covariance-based sensitivity indices (SI) are also used, compared to variance-based SI. Furthermore, we emphasize covariance decomposition can be generalized in a straightforward way to decompose high order moments.

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Solar greenhouses are currently the most energy-intensive agricultural sector. In literature, there is no worldwide mapping of solar greenhouse performance under different climate scenarios. This study analyzes the performance of a Venlo solar greenhouse for 48 localities around the world. Solar greenhouses are mainly made of a transparent envelope and the effect of the direct and diffuse component of solar radiation impacts the internal plant well-being. This study aims to identify the best solution of a transparent envelope on locations with different latitudes and evenly distributed around the globe. The simulations are carried out using TRNsys, considering different thermal phenomena three-dimensional shortwave and longwave radiative exchange, airflow exchanges, presence of lamps with their exact 3D position, ground, plant evapotranspiration, and convective heat transfer coefficients. A total of 336 simulations are performed in the free-floating regime. A new index for the identification of the best glass solutions based on annual average deviation is defined. For all climates, the best glass solutions work better in winter than in summer. The optimal choice of the glass must be combined with effective scheduling of openings for natural ventilation to avoid internal overheating phenomena.

This work presents a new protocol for monitoring rising damp, which is applied to three masonry models made of tuff, carparo, and Lecce stone. First, the physical characteristics of each stone were derived in the laboratory, which included porosity, imbibition, drying index, permeability, capillarity, and sorptivity. In this case, the protocol provided three columns, one for each material, consisting of five blocks. A layer of cotton tissue was interposed between columned blocks to simulate the hygroscopic behavior of a mortar, allowing a quick disassembly and reassembly of the multiblock columns for a quick weighing. The bottoms of the columns were immersed in water to a level of about three centimeters, providing a constant replenishment for the phenomena of evaporation and rising in the stone. The maximum height achieved by the rising damp depends on the characteristics of the building materials, i.e., the amount and size of pores, pore connectivity, etc. Since these materials have different physical characteristics, the objective was to quantify the rising moisture level of the three materials tested, block by block, in a controlled indoor microclimate environment. The three columns were periodically weighed, the quantity of collected water was evaluated, and a thermographic survey was performed. The results show that at the end of the test, the highest level of rising damp is reached by tuff with a height of 43 cm, followed by Lecce stone and carparo with a height of 40 cm and 21 cm, respectively. The innovation of this study is the proposal of a new flexible and easy-to-apply method for monitoring this phenomenon. It gives clear and numerically comparable results. Moreover, it is applicable to any type of stone, allowing the user to evaluate both the existing state and different design solutions.

Thermal modeling of building components plays a crucial role in designing energy efficiency measures, assessing living comfort, and preventing building damages. The accuracy of the modeling process strongly depends on the reliability of the physical models and the correct selection of input parameters, especially for historic buildings where uncertainties on wall composition and material properties are higher. This work evaluates the reliability of building thermal modeling and identifies the input parameters that most affect the simulation results. A monitoring system is applied to a historic building wall to measure the temperature profile. The long-term dataset is compared with the result of a simulation model. A sensitivity analysis is applied for the determination of the influential input parameters. A two-step optimization is performed to calibrate the numerical model: the first optimization step is based on an optimized selection of the database materials, while the second optimization step uses a particle swarm algorithm. The results indicate that the output of the simulation model is largely influenced by the coefficients describing the coupling with the boundary conditions and by the thermal conductivities of the materials. Very good results are obtained already after the first optimization step (RMSE=0.75°C) while the second optimization step improves further the agreement (RMSE=0.48°C). The parameter values reported in the datasheets do not match those found through optimization. Even with extensive optimization using an algorithm, starting with monitoring data is insufficient to identify material parameter values.

Ensuring optimum interior lighting is a topic of great importance, as this influences not only the well-being of users but also the optimal performance of visual tasks. Lighting can be natural, but if not sufficient, it can be compensated with artificial lighting. This study highlights a methodology for designing a new lighting system that takes into account both technical and economic aspects. The method was applied to an existing school located in southern Italy, in which the electricity consumption is related to the current lighting system. The school is chosen as being representative of the construction type and layout of many local schools. In addition, the coexistence of several visual tasks with different design requisites (e.g., illuminance levels) makes the school a very complex environment. The school lighting is modelled in Google SketchUp and imported into Daysim to simulate the yearly and hourly daylight indoor contribution. Dialux Evo has been used to simulate and design artificial lighting. The results show a reduction of energy consumption of 33% with the simple replacement of fluorescent luminaires with LEDs, while the LED lamp dimming and modulation for rows of luminaires leads to a 95% reduction in energy consumption compared with the current state.

Rising damp is considered one of the most widespread and damaging deterioration processes in buildings, architectural and cultural heritage. A widespread lack of knowledge of this phenomenon has often led to inadequate corrective measures with the consequent accelerated masonry deterioration. This work focuses on the dynamic evaluation of rising damp in two typical and widely used building stones in Southern Italy (Salento peninsula): Lecce Stone and Carparo. Under controlled and monitored microclimatic conditions, an experimental campaign has been carried out in laboratory, starting from two dry monolithic blocks. The blocks were periodically wetted, weighed and the height of rising damp measured in the tested materials. At the end of the campaign, the rising damp behaviour has been derived using the well-known mathematical model of Christopher Hall and William D. Hoff. Finally, the theoretical model was adapted to the case study, modifying the model constants based on the collected experimental data. The results were analysed, and the study showed a good agreement between the numerical and experimental data in both tested materials.

Hygrothermal simulations are expected to provide powerful support to the design process in the context of energy retrofit of historic buildings and prevent the moisture-related damages. They can be used to predict the hygrothermal behaviour of the building in detail and exclude the occurrence of moisture related damages, such as mould formation or material degradation. However, these simulations require various input data related to materials and boundary conditions, which are often difficult to find during the design phase. In this article we analyse the potential of hygrothermal simulations in predicting the hygrothermal behaviour of an internally insulated wall, even with limited information on the hygrothermal properties of the materials composing the historical wall. The quality of the simulation's results is evaluated through a comparison with monitored data. The numerical model is calibrated to maximise the agreement with the monitored data. The considered case study is a historical building located nearby Bolzano (Northern Italy). The monitoring system is installed with the aim of analysing temperature and relative humidity profiles within the construction. In addition, the climatic boundary conditions are measured both inside and outside the building, including temperature, relative humidity, driving rain and solar radiation. The numerical simulation of the wall under analysis is performed with the software DELPHIN.

Around the world, expected climate changes can affect indoor comfort conditions in buildings. Analysing the climate in which buildings are located is the first step towards high-efficiency design, and today it is no longer possible to ignore impending climate change. This study has provided a worldwide picture of how comfort conditions inside a building can change as external climatic conditions change. For the first time, a building is tested worldwide over a long-term period, and not just in a specific climate or a small group of climates. Several cities homogeneously distributed around the world were selected, covering all climates of the Koppen-Geiger classification. A hypothetical building was implemented with the Termolog Epix 11 software in order to monitor the operative temperature (TOP) in free-floating mode on an hourly basis and test its temperature variations in the short, medium and long term. The percentage values of the hours when the TOP is in a comfort or discomfort conditions were compared for all configurations. The results showed that the comfort conditions vary with the climate. Climate zone A displayed for most subclimates high TOP values. Climate zone B showed an irregular trend, from 2020 to 2080 the hours when TOPs fall below 20 °C decreased in most locations. Climate zone C included areas where TOPs are mostly in the comfort range. Some sub-climates in zone D show very cold climates, with an average of about 15–20% of the annual hours in the comfort zone in 2020, then increasing slightly by a few percentage points in 2080.

Greenhouse crops represent a significant productive sector of the agricultural system, one of the main problems to be addressed is indoor air conditioning to ensure thermal well-being of crops. This study focuses on the ventilation analysis of solar greenhouse with symmetrical flat pitched roof and single span located in a warm temperate climate. This work proposes the dynamic analysis of the greenhouse modeled in TRNsys, simultaneously considering different thermal phenomena three-dimensional (3D) shortwave and longwave radiative exchange, airflow exchanges, presence of lamps with their exact 3D position, ground and plant evapotranspiration, and convective heat transfer coefficients. Several air conditioning systems were analyzed, automatic window opening, controlled mechanical ventilation systems (CMV) and horizontal Earth-to-Air Heat Exchanger (EAHX) coupled with CMV, for different air volume changes per hour. In summer, the exploitation of the ground allows having excellent results with the EAHX system, reducing the temperature peaks of up to 5 &deg, C compared to the use of CMV. In winter, it is interesting to note that, although the EAHX is not the solution that raises the temperature the most during the day, its use allows flattening the thermal wave more. In fact, the trend is almost constant during the day, raising the temperature during the first and last hours of the day.

Zero Energy Buildings (ZEBs) are expected to play a significant role in reducing energy consumption and combating climate change. Despite this awareness, there is a lack of approaches and indicators at the regulatory level to quantify the long-term potential of strategies applied to buildings today. This study concerns the dynamic thermal modeling over the years, until 2080, of a multi-residential building located in Lecce, a city in southeastern Italy, characterized by a Mediterranean hot summer climate. Over time, Italian legislation has brought increasingly stringent limits on the design of the building envelope. Although with different regulatory limits, in the different climates across Italy, a growing trend towards a more insulated envelope, characterized by very low transmittances, has been observed over the years. This study shows how, in hot climates, buildings constructed within the legal limits will suffer from overheating over the years, necessarily leading to a disproportionate, and more extensive, use of cooling systems throughout the year. This study proposes a critical analysis of the long-term effectiveness of national strategies applied to the building envelope to date to achieve the ZEB goal, emphasizing that long-term predictive analyses become relevant in current building design and should be considered in regulations.

The European Energy Performance of Buildings Directive (EPBD) recast proposes, a comparative methodology to calculate cost-optimal levels of minimum energy performance requirements for buildings. This paper presents a method able to select the best retrofit action for lighting system, selectively analysing the daylight conditions and applying the cost-optimal methodology for different scenarios proposed for two existing educational buildings located in Italy. With the aim to improve both energy efficient and visual comfort conditions, the retrofit scenarios include lighting solutions with different combinations. They consider the replacement of lamps with more efficient lighting sources and the application of lighting control.

This paper investigates the performance of a 960 kWP photovoltaic (PV) system, located in southern Italy. Monitoring data over a 43 months period are used to evaluate the monthly average of energy yields, losses and efficiency. The performance ratio and the capacity factor were 84.4% and 15.6%, respectively. The yearly average module efficiency was 15.3% and the system efficiency was 14.9%, whereas the capture and system losses were 0.6 h/day and 0.1 h/day respectively. The degradation rate of the PV system, after continuous outdoor exposure, has been estimated at about 1.48%/year by applying the Classical Seasonal Decomposition (CSD) method. A comparison in terms of degradation rate is made with other PV plants installed in different climates to address the need of standard methods to determine this crucial parameter. The actual performance of the studied PV system is compared with the expected outcomes by using two widely used PV simulation tools, SAM and PVsyst. A detailed difference analysis is carried out to evaluate the accuracy of the SAM and PVsyst models. Results show that the yearly average energy injected into the grid was under-estimated by 3.0% by SAM and by 3.3% by PVsyst, but overall PVsyst outperforms the SAM tool. Results provide reliable data on the plant and demonstrate its good performance compared to other plants located in the same climate. The results can be used to improve the prediction of the performance of future PV of systems in the Mediterranean climate, and also provide a useful dataset for comparative studies.

There is not a real “storage market” and the range of technical solutions for electrical storage appears to be underdeveloped. The use of electrochemical batteries seems to be the easiest and cheapest way, but some problems related to disposal, average life span and storage capacity, still put a brake on their diffusion. The micro CAES-TES (Compressed Air Energy Storage – Thermal Energy Storage) systems with small renewable energy plants for cogeneration and trigeneration represent an important development perspective thank to the reuse of the heat generated at the stage of air compression (for heating) and air expansion (for cooling). This improves the complexity of the entire system because of the heat exchange and thermal storage units must match the capacities and performances of the air compression/expansion units. The paper presents a new mathematical model for micro CAES-TES systems, implemented in Matlab software environment. The novelty is the use of air compressed energy storage in small and residential applications, a trigeneration due to reuse of heat from air compression and expansion stage, only renewable energy used. By keeping the initial investment low, the analysis is extended to the optimal system configuration and identifies key parameters that have a dominant influence on improving system efficiency and provides useful guidance for CAES-TES system design. The results show that, for an air storage volume of 4 m3, the optimal configuration is with a compression ratio of 15 splitted in two stages, charging time 5 h, mechanical storage efficiency 48%, compression air flow rate 3.73 kg/hour. The proposed system has a possible future development overall if combined with new possible scenarios of direct use of compressed air in the residential sector.

This work proposes a new device for air treatment with dehumidification and water recovery/storage, with possible mitigation of indoor environmental conditions. The system is based on Peltier cells coupled with a horizontal earth-to-air heat exchanger, it is proposed as an easy-to-implement alternative to the heat pumps and air handling units currently used on the market, in terms of cost, ease of installation, and maintenance. The process provides the water collection from the cooling of warm-humid air through a process that leads to condensation and water vapor separation. The airflow generated by a fan splits into two dual flows that lap the two surfaces of the Peltier cells, one flow laps the cold surfaces undergoing sensible, latent cooling with dehumidification; the other flow laps the hot surfaces and heats up. The airflow undergoes thermal pre-treatment through the underground horizontal geothermal pipe that precedes the Peltier cells. In the water storage tank, which also works as a mixing chamber, the two air streams are mixed to regulate the outlet temperature. The system can be stand-alone if equipped with a photovoltaic panel and a micro wind turbine, able to be used in places where electricity is absent. The system, with different configurations, is modeled in the African city Kigali, in Rwanda.