Influence of the underneath cavity on buoyant-forced cooling of the integrated photovoltaic panels in building roof: a thermography study

Airflow around building-integrated photovoltaics (BIPV) has a significant impact on their hygrothermal behavior and degradation. The potential of reducing the temperature of BIPV using an underneath cavity is experimentally and numerically investigated in literature. Most of the models are oversimplified in terms of modeling the impact of 3D flow over/underneath of PV modules, which can result in a non-uniform surface temperature and consequently a non-homogenous thermal degradation. Moreover, the simultaneous presence of radiation and convection related to upstream wind, in addition to the combined impact of back-ventilation and surface convection, is barely addressed in literature. However, these simplifications can result in the unrealistic loading climate conditions. This paper aims to present a unique experimental setup to provide more realistic climate conditions for investigating the ventilation potential of the underneath. The setup consists of a solar simulator and a building prototype with installed PV, placed inside an atmospheric wind tunnel to control upstream wind velocity. Thermography is performed using an infrared camera to monitor the surface temperature of the BIPV. The potential of an underneath cavity with various cavity heights and PV arrangement is further investigated in this paper. The outcome would be eventually useful in the development of practical guidelines for BIPV installation. Copyright © 2013 John Wiley & Sons, Ltd

Validation of a Climatic CFD Model to Predict the Surface Temperature of Building Integrated Photovoltaics

AbstractThe current market of the photovoltaic (PV) industry is dominated by silicon-based modules, which are malfunctioned and degraded in higher temperatures mainly above 25°C. Consequently, one of the challenges for such modules is finding a more efficient way in their integration into the buildings in order to reduce the mentioned temperature. The present work is a part of a comprehensive framework toward the investigation of the lifetime durability of the BIPV modules. Therefore, this paper explain the development and validation of a computational fluid dynamics (CFD) model to be later utilized to evaluate the temperature distribution of BIPV's surfaces under different arrangements and climate loadings. For this purpose, a high resolution 3D CFD model is firstly developed by generation of about 3 million cells. Then, the model is validated with a velocimetry experimental dataset from the same model tested in a wind tunnel experiment by [6]. Furthermore, the solar radiation is added into simulation to model the non-isothermal condition of the BIPV module. The non-isothermal case is further validated with a thermography observation conducted by [5] where a solar simulator is installed inside the tunnel. The simulation results show that the developed model can accurately simulate the impact of 3D flow over/underneath the PV modules

A new regression model to predict BIPV cell temperature for various climates using a high-resolution CFD microclimate model

Understanding of cell temperature of Building Integrated Photovoltaics (BIPV) is essential in the calculation of their conversion efficiency, durability and installation costs. Current PV cell temperature models mainly fail to provide accurate predictions in complex arrangement of BIPVs under various climatic conditions. To address this limitation, this paper proposes a new regression model for prediction of the BIPV cell temperature in various climates and design conditions, including the effects of relative PV position to the roof edge, solar radiation intensity, wind speed, and wind direction. To represent the large number of possible climatic and design scenarios, the advanced technique of Latin Hypercube Sampling was firstly utilized to reduce the number of investigated scenarios from 13,338 to 374. Then, a high-resolution validated full-scale 3-dimensional Computational Fluid Dynamics (CFD) microclimate model was developed for modelling of BIPV’s cell temperature, and then was applied to model all the reduced scenarios. A nonlinear multivariable regression model was afterward fit to this population of 374 sets of CFD simulations. Eventually, the developed regression model was evaluated with new sets of unused climatic and design data when a high agreement with a mean discrepancy of 3% between the predicted and simulated BIPV cell temperatures was observed

Simplified model to predict the thermal demand profile of districts

Extensive research works have been carried out over the past few decades in the development of simulation tools to predict the thermal performance of buildings. These validated tools have been used in the design of the building and its components. However, limited simulation tools have been developed for modeling of district energy systems, which can potentially be a very laborious and time-consuming process. Besides many associated limitations, providing a realistic demand profile of the district energy systems is not a straightforward task due to high number of parameters involved in predicting a detail demand profile. This paper reports the development of a simplified model for predicting the thermal demand profile of a district heating system. The paper describes the method used to develop two types of simplified models to predict the thermal load of a variety of buildings (residential, office, attached, detached, etc.). The predictions were also compared with those made by the detailed simulation models. The simplified model was then utilized to predict the energy demand of a variety of districts types (residential, commercial or mix), and its prediction accuracy was compared with those made by detailed model: good agreement was observed between the results

Experimental and Steady-RANS CFD Modelling of Cross-ventilation in Moderately-dense Urban Areas

Computational fluid dynamics (CFD) models based on the steady Reynolds-averaged Navier Stokes (SRANS) equations are vastly used for calculation of airflow field inside and around cross-ventilated buildings. However, most of the developed CFD guidelines ignore CFD challenges related to cross-ventilation modeling in terms of flow unsteadiness, high level of gradients of airflow parameters, and complex interactions between the indoor and outdoor flows.Hence, a systematic parametric study was performed in this study for a generic cross-ventilated building model with a planar area ratio of 0.25 against different wind angles while effects of different CFD parameters, including advection and diffusion terms discretization methods, mesh generation techniques, and turbulence models on prediction accuracy and convergence behavior of CFD solver were comprehensively studied.Results show that a particularly generated unstructured tetrahedral mesh configuration with significantly lower mesh numbers can provide comparable results with structured hexahedral mesh configuration. Furthermore, second-order discretization scheme for advection terms encounters convergence issues against the normal wind angle, but generally presents more accurate results against oblique wind angles. Moreover, two-equation turbulence models showed very low accuracy in the case of normal wind angle, but acceptable results were found for oblique wind angles

Developing a framework for improvement of building thermal performance modeling under urban microclimate interactions

Coupled models developed from the building energy simulation (BES) and computational fluid dynamics (CFD) methods are occasionally used for analyzing the buildings thermal performance. Nevertheless, the large uncertainty in the input parameters of BES models and values of the closure coefficients of Reynolds-averaged Navier-Stokes (RANS) turbulence models restrict the accuracy of coupled BES-CFD models for thermal performance prediction in highly dense urban areas.Thus, a systematic framework for improving the accuracy of the coupled BES-CFD models is proposed in this study, consisting of an approximation technique and a stochastic optimization approach. In this framework, at first, a CFD model is improved with a closure coefficients optimization procedure using experimental data. In the second step, the improved CFD model is utilized to conduct a series of CFD simulations for real-geometry buildings in order to calibrate the BES model with the alteration of parameters such as the adaptive discharge coefficient, local wind profile, and convective heat transfer coefficients over the building façades.The developed framework is then applied to a small cross-ventilated office building surrounded by neighboring buildings. Deviations up to 60% are found in the prediction of the energy saving potential of cross-ventilation strategy by the default and calibrated BES models

Development of a dynamic external CFD and BES coupling framework for application of urban neighbourhoods energy modelling

© 2018 Elsevier Ltd Current building energy models are weak at representing the interactions between neighbourhoods of buildings in cities. The effect of a neighbourhood on the local microclimate is complex, varying from one building to another, meaning that neighbourhood effects on the airflow around a particular building. A failure to account for this may lead to the miss-calculation of heat transfer and energy demand. Current building energy simulation (BES) tools apply convective heat transfer coefficient (CHTC) correlations, which were developed by using a simplified model of wind flow that neglects neighbourhood effects. Computational Fluid Dynamics (CFD) techniques are able to model these neighbourhood effects and can be used to improve CHTC correlations. This work aims to develop a framework that couples CFD and BES tools to enhance the modelling of outdoor convective heat transfer in different urban neighbourhoods. A dynamic external coupling method was used to combine the benefits from both domains. Firstly, a microclimate CFD model was validated before the coupling stage using wind tunnel data. Secondly, the framework was tested using a benchmark model of a building block. Fully converged values of the surface temperature and CHTC were achieved at each time-step by the BES and CFD domains. The results highlight the importance of neighbourhood effect while the prediction of the hourly averaged external convection using coupling method can amend the simulation by up to 64% comparing to the standalone conventional BES models with DOE-2 CHTC approach

Optimization of a hybrid community district heating system integrated with thermal energy storage system

Evidence from a various research suggests that buildings hold a vital role in climate change by significantly contributing to the global energy consumption and the emission of greenhouse gases. Considering the trend of higher energy consumption in the building sector, it is important to influence this sector by decreasing its energy demand. District generation and cogeneration systems integrated with the energy storage system have been suggested as a potential solution to achieve such planned goals. Unlike the older generation of the DHS, where the focus of the design was on minimizing the system heat loss, in 4th generation DHS, achieving higher system efficiency is made possible by picking the optimal equipment size as well as adopting the appropriate control strategy. Designers have adopted different design methods for selecting the equipment size, however, finding the optimal size is a challenging task. This paper reports the development of a simplified methodology (dynamic optimization) for a hybrid communitydistrict heating system (H-CDHS) integrated with a thermal energy storage system by coupling the simulation and optimization tools together. Two, existing and newly built communities, have been considered and the results of the optimization on the equipment size of both communities have been studied. The results for the newly built community is later compared with the one obtained from the conventional equipment size methods whereas static optimization methods and potential size reduction with the conventional method has been obtained

Fast and dynamic urban neighbourhood energy simulation using CFDf-CFDc-BES coupling method

Building energy simulation (BES) tools show limitations in calculations of the convective heat transfer exchange with the surrounding urban areas. Therefore, dynamic coupling of BES to computational fluid dynamics (CFD) techniques is a common strategy to improve the simulation performance. Nonetheless, dynamic coupling itself is understood to be computationally intensive and unaffordable even in simplistic neighbourhood-scale scenarios.This paper proposes a novel framework for integration of a high-resolution CFD model (CFDf) into a coupled model of low-resolution CFD (CFDc) and BES. In specific, the CFDf model (fine grids) operates as the off-line component in the whole procedure that provides the boundary conditions, including the flow patterns, to CFDc (coarse grids) at the openings in the form of the mass flow information to BES to start the iterative process. After that, CFDc and BES domains execute a fully dynamic external coupling to deliver an accurate energy simulation.A case study is designed for a simple neighbourhood on a typical hot day for sheltered buildings with night-purge cooling. The results highlight in a significant improvement in results with representing neighbourhood effect and in a substantial reduction of computation cost of the dynamic coupling procedure

A review and critique of UK housing stock energy models, modelling approaches and data sources

The UK housing stock is responsible for some 27% of national energy demand and associated carbon dioxide emissions. 80% of this energy demand is due to heating (60%) and domestic hot water (20%), the former reflecting the poor average thermal integrity of the envelope of the homes comprising this stock. To support the formulation of policies and strategies to decarbonise the UK housing stock, a large number of increasingly sophisticated Housing Stock Energy Models (HSEMs) have been developed throughout the past 25 years. After describing the sources of data and the spatio-temporal granularity with which these data are available to represent this stock, as well as the physical and social phenomena that are modelled and the range of strategies employed to do so, this paper evaluates the 29 HSEMs that have been developed and deployed in the UK. In this we consider the models' predictive accuracy, predictive sensitivity to design parameters, versatility, computational efficiency, the reproducibility of predictions and software usability as well as the models' transparency (how open they are) and modularity. We also discuss their comprehensiveness. From this evaluation, we conclude that current HSEMs are lacking in transparency and modularity, they are limited in their scope and employ simplistic models that limit their utility; in particular, relating to the modelling of heat flow and in the modelling of household behaviours relating to investment decisions and energy using practices. There is a need for an open-source and modular dynamic housing stock energy modelling platform that addresses current limitations, can be readily updated as new (e.g. housing survey) calibration data is released and be readily extended by the modelling community at large: improving upon the utilisation of scarce developmental resources. This would represent a considerable step forward in the formulation of housing stock decarbonisation policy that is informed by sound evidence