123 research outputs found
Performance assessment of hygrothermal modelling for diagnostics and conservation in an Italian historical church
The hygrothermal modelling of historical churches is a promising approach to study preservation issues and suitable retrofit measures. However, difficulties can arise in the use of Heat, Air and Moisture (HAM) models, which are often customised objects to be integrated into validated building energy simulation (BES). This research outlines a multi-step methodology to investigate the capability of a BES software coupled with a HAM model (BES + HAM) as a technique for diagnostics and conservation in complex settings. The 17th-century church of Santa Rosalia (Italy) was used as a historical site in a real context. As first step, the performance of the simulation tool was analysed through standardised exercises aiming at excluding incorrect assumptions and calculations in the HAM model (HMWall). Secondly, a building model of the church using a 1D heat transfer model (named building model A) was compared with one using HMWall (named building model B) in terms of the accuracy of the indoor climate simulations against hygrothermal measurements. The results showed that building model B enhanced the simulation accuracy by +50% with respect to building model A. Finally, annual simulations inside the church were run to further compare the seasonal trends of indoor climate scenario obtained from the two building models. Building model B allowed to study the water content distribution inside the altarpiece and a wall partition, showing that BES + HAM tools can be used to identify potential moisture-induced conservation risks
Data validation and uncertainty evaluation of the ESTER outdoor facility for testing of PV modules
In the paper the uncertainty analysis of the FTA Lab ESTER facility instrumentation is presented together with the procedure used to validate data outputs through measurements on a reference polycrystalline module provided by ISAAC-SUPSI. The reference module has been tested for several months and a procedure has been identified to sort the IV
curves for translation at STC conditions. Blaesser method has been implemented and comparison between STC data from indoor measurements by ISAAC and translated outdoor curves produced quite satisfactory results
Outdoor characterization of dye solar cells: first results
The Centre for Hybrid and Organic Solar Energy (CHOSE) at the University of Rome Tor Vergata is focusing
its efforts in developing reliable and stable dye solar cells and modules. The CHOSE development program foresees that new cells and modules will be tested both indoor and outdoor in order to have an overview of the real performances of the devices. This is generally a key point for a correct evaluation of the actual performances of any photovoltaic technology. In
October 2008 an outdoor measurement campaign on Dye Solar Cells has been started. Two different types of cells have been built in the laboratory, varying the characteristics of the TiO2 film, in order to evaluate their behaviour in real outdoor
environment. Data collected during the two first month of outdoor cell exposure are presented in this paper. Daily trends of cell efficiency as a function of the environmental parameters and of the cell temperature have been investigated, focusing on
the cell behaviour at low irradiance levels
Advanced results of modelling, experiments, and innovative solar energy components conceived at FTA laboratories
Preliminary study of the mechanical and hygrothermal performance of concrete reinforced with fibrillated cellulose
Cement, being the most widely used building material, is the responsible for a large share of greenhouse gas emissions. To reduce the environmental impact of its production, natural fibres can be used as eco-friendly additives. Moreover, their potential use in traditional lime-based mortars makes them an ideal choice for green buildings as well as for the retrofit of historical buildings. An innovative cementitious composite reinforced with fibrillated cellulose (hereafter called «green concrete») was tested to assess its mechanical and physical properties. Samples were casted using Portland cement and natural hydraulic lime and varying the ratios among the constituents. Viscosity and setting time of the fresh pastes were determined with a viscosimeter and a Vicat apparatus, while their hydration was studied by thermal analysis. The influence of the fibres on the flexural strength of the final composite was determined through mechanical tests. The expected hygrothermal performance of the «green concrete» was explored through dynamic hygrothermal simulation to investigate its potential use as a retrofit material. A sensitivity analysis (SA), based on the hygrothermal properties of natural-based building materials similar to the «green concrete», was conducted to identify the parameters influencing more the simulation of annual internal temperature and moisture variations. The preliminary assessment of the mechanical properties of the «green concrete» showed that at higher percentages the cellulose fibres can negatively affect the workability/setting time of the fresh pastes and the flexural strength. The most promising samples were identified and will undergo further investigation. The SA results outlined that the «green concrete» might not be effective for thermal insulation, although it might be used as a moisture-buffering layer by adjusting the values of the free water saturation moisture content, the equilibrium moisture content at RH=80% and the dry vapour diffusion resistance factor of the final composite
Calibrating the Dynamic Energy Simulation Model for an Existing Building: Lessons Learned from a Collective Exercise †
Calibration of the existing building simulation model is key to correctly evaluating the energy savings that are achievable through retrofit. However, calibration is a non-standard phase where different approaches can possibly lead to different models. In this study, an existing residential building is simulated in parallel by four research groups with different dynamic simulation tools. Manual/automatic methodologies and basic/detailed measurement data sets are used. The calibration is followed by a validation on two evaluation periods. Monitoring data concerning the windows opening by the occupants are used to analyze the calibration outcomes. It is found that for a good calibration of a model of a well-insulated building, the absence of data regarding the users' behavior is more critical than uncertainty on the envelope properties. The automatic approach is more effective in managing the model complexity and reaching a better performing calibration, as the RMSE relative to indoor temperature reaches 0.3 degrees C compared to 0.4-0.5 degrees C. Yet, a calibrated model's performance is often poor outside the calibration period (RMSE increases up to 10.8 times), and thus, the validation is crucial to discriminate among multiple solutions and to refine them, by improving the users' behavior modeling
Progress in regional PV power forecasting: A sensitivity analysis on the Italian case study
The increasing penetration of PV generation, driven by climate strategies and objectives, calls for accurate
production forecasting to mitigate the negative effects associated with inherent variability, such as
overgeneration, grid instability, supplementary reserve request. The regional PV power forecasting is
crucial for Transmission and Distribution system operators for a better management of energy flows. In
this work many aspects of regional PV power forecasting are investigated, by means of a comparison of
six different forecasting models applied to predict the hourly production of the following days on six
Italian bidding zones for one year. In particular, the work shows that the forecasting accuracy is mainly
affected by the algorithm and its pre and post processing, with a range of 30% in performance accuracy,
while it is less impacted by the forecasting horizon. It has been verified that the accuracy in the irra-
diation prediction, used in input to the power forecasting algorithm, has less impact compared to single
plants. The work confirms the performance improvement which can be obtained by increasing the size of
the area to which the prediction refers, through a comparison between the forecasting at bidding zone
and national level. Finally, we show that the larger the controlled forecast area, the smaller the impact on
the forecast accuracy due to the non-uniform spatial and capacity distribution of the PV fleet. This means
that as the size of the region increases, the average irradiance progressively becomes the best PV power
predictor. We refer to this phenomenon as: “input smoothing effect"
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