• Energy Research

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Abstract Lighting systems have a fundamental role for the overall buildings energy consumption. Therefore, remarkable efforts are required for optimizing the lighting systems energy use and for finding new daylight harvesting solutions. In this paper, the impacts on daylight harvesting provided by different room and window geometries and their effects on energy savings are presented. An academic classroom with only one window is chosen as case study and it is supposed that the window orientation is modified according to the four cardinal points. A climate-based approach was chosen for the multiple simulations, carried out via DIVA software, by assuming: square and rectangular classroom geometries with the same total area; square and rectangular window shapes having Window to Floor Ratios (WFRs) equal to 8% and 12%; two different dimmable lighting systems, in order to quantify the energy savings, by considering fluorescent and LED dimmable lamps. The daylight analysis, performed by evaluating both the Daylight Factor (DF) and the Daylight Autonomy (DA), showed that room and window geometries have high influence on daylight harvesting maximization, allowing remarkable energy savings (up to 48.5%) with respect to non-dimmable lighting system. In particular, the best energy result, equal to 467.5 kWh/yr, was obtained with rectangular room and window geometries coupled with LED lamps and WFR equal to 12%.

Appropriate daylight control could maximize occupants’ visual comfort, potentially saving energy. However, the deployment of daylight control systems (DLCSs) is not happening, mainly due to the complex system calibration and the frequent reluctance of occupants toward automatic control systems that exclude their participation. In this paper, a human-in-the-loop DLCS is presented. The system is designed to allow the users to have direct interaction via smartphone Bluetooth communication, enabling them to set the lighting values deemed most comfortable nimbly. Special attention has been paid to the power consumption of the DLCS, especially in standby mode. Accessibility of configuration has been taken into consideration, leading to the choice of a wireless configured device. The performance of the prototype DLCS was evaluated experimentally in a side-lit room and compared with that of a commercial controller. The illuminance on a reference work plane was measured during the operation of the systems to observe the controllers’ effect on the lamp’s luminous flux while simultaneously considering the variation of daylight conditions. Moreover, the energy performance of the systems was studied to obtain information about the energetic effectiveness and convenience of the studied DLCSs. The main results showed that the proposed system could maintain the required target illuminance values on the work plane as daylight conditions vary: the maximum deviation measured using the prototype never exceeded 11 lx. In comparison, the commercial controller reached peaks of 220 lx. Moreover, the energy consumption of the prototype (resulting equal to 370 mVA) was lower than the consumption of the commercial system (equal to 600 mVA), allowing for increased energy savings over the long period. The more straightforward configuration allows the user to better interact with the DLCS.

In this paper, a novel integrated measuring and control system for hot box experiments is presented. The system, based on a general-purpose microcontroller and on a wireless sensors network, is able to fully control the thermal phenomena inside the chambers, as well as the heat flux that involves the specimen wall. Thanks to the continuous measurements of air and surfaces temperatures and energy input into the hot chamber, the thermal behavior of each hot box component is analyzed. A specific algorithm allows the post-process of the measured data for evaluating the specimen wall thermal quantities and for creating 2D and 3D thermal models of each component. The system reliability is tested on a real case represented by a double insulating X-lam wall. The results of the 72 h experiment show the system’s capability to maintain stable temperature set points inside the chambers and to log the temperatures measured by the 135 probes, allowing to know both the U-value of the sample (equal to 0.216 ± 0.01 W/m2K) and the thermal models of all the hot box components. The U-value obtained via hot box method has been compared with the values gathered through theoretical calculation and heat flow meter measurements, showing differences of less than 20%. Finally, thanks to the data postprocessing, the 2D and 3D thermal models of the specimen wall and of the chambers have been recreated.

Abstract The building energy behavior is strongly influenced by design choices made to contain energy losses through the envelope and to maximize the overall efficiency of HVAC systems. However, a thorough assessment of energy efficiency measures in relation to weather conditions is necessary. Ongoing climate change requires that design choices be also assessed in relation to projections of their future state. In this paper, the heating performance of real-world energy self-sufficient building, located in L’Aquila (Italy), is analyzed via calibrated EnergyPlus model. Different interventions are hypothesized for the HVAC system (biomass boiler, air handling unit, condensing gas boiler, air-to-water heat pump, their combinations) and effects are tested in relation to climate zone, by four Italian (L’Aquila, Rome, Palermo, Milan) and two European (Madrid, London) cities, and considering climate change to 2050 and 2080 for the city of L’Aquila. Results showed how heating system is influenced by weather conditions and what are the best choices in relation to them, ranging from 3.0 kWhm−2yr−1, achieved with combination of condensing gas boiler and air handling unit, to 54.2 kW hm−2yr−1, obtained with air-to-water heat pump. Finally, future climate change has highlighted significant reductions in heating energy demand between −8.5 % (2050) and −44.8 % (2080).

Building Information Modeling (BIM) and Building Energy Modeling (BEM) can revolutionize the building design process, enabling early-stage energy analysis and sustainable design. However, effective interoperability between these tools remains a significant challenge. This paper investigates two strategies for bridging the gap between BIM and BEM: real-time connection (S1) and standardized exchange formats (S2). A case study building was employed to compare the performance of these approaches, and all dynamic energy simulation models were calibrated using statistical analysis of experimental thermal energy consumption data. While S1 proved to be limited by customization constraints and consequently not applicable for the case study selected, S2 demonstrated successful interoperability, yielding energy-calibrated model results consistent with traditional BEM methods, with a difference of only 2 % in annual thermal energy consumption obtained. This work, concretely testing the BIM-to-BEM approach, is able to suggest practical actions to improve communication between software where possible. Furthermore, the direct comparison between the different approaches to modeling allows to clearly highlight the advantages and disadvantages of each one, underlining the importance of reliable data exchange for accurate energy simulations and the need for further advancements in BIM-to-BEM interoperability to fully realize the benefits of integrated design.

The evaluation of photovoltaic (PV) system’s efficiency loss, due to the onset of faults that reduce the output power, is crucial. The challenge is to speed up the evaluation of electric efficiency by coupling the electric characterization of panels with information gathered from module diagnosis, amongst which the most commonly employed technique is thermographic inspection. The aim of this work is to correlate panels’ thermal images with their efficiency: a “thermal signature” of panels can be of help in identifying the fault typology and, moreover, for assessing efficiency loss. This allows to identify electrical power output losses without interrupting the PV system operation thanks to an advanced PV thermography characterization. In this paper, 12 faulted working panels were investigated. Their electrical models were implemented in MATLAB environment and developed to retrieve the ideal I-V characteristic (from ratings), the actual (operative) I-V characteristics and electric efficiency. Given the curves shape and relative difference, based on three reference points (namely, open circuit, short circuit, and maximum power points), faults’ typology has been evidenced. Information gathered from infrared thermography imaging, simultaneously carried out on panels during operation, were matched with those from electrical characterization. Panels’ “thermal signature” has been coupled with the “electrical signature”, to obtain an overall depiction of panels’ health status.