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Over the past decade, the building energy research community has increasingly focused on urban-scale models. The shortcomings of analyzing isolated buildings in an urban context are well-known and far from negligible, mainly due to the inability to account for Urban Heat Island (UHI), shading from neighboring obstructions, and obstructed wind flow. The aim of this paper is to evaluate the impact of the urban context via urban-scale modelling and inverse parameter estimation (calibration) using metered building energy consumption. We describe an automated calibration process for modelling 56 buildings in a representative district in downtown Abu Dhabi (UAE), where a detailed energy audit was conducted with data from 2008 to 2010. Since the urban ambient air temperature could differ significantly from the reference rural air temperature used in most building simulations, the calibration procedure will also consider this UHI effect. Two main approaches of district-wide energy model calibration are proposed using a genetic algorithm and compared to a baseline case where UHI is not considered. The first approach estimates seven building-related parameters together with four microclimate-related variables (describing annual average and seasonal variation of the UHI effect on both air temperature and humidity). The second one uses the Urban Weather Generator (UWG) to pre-process the urban EPW file, thereby reducing the number of the parameters to be estimated. In addition, two approaches are investigated for the calculation of the ASHRAE Guideline 14 calibration error metrics (CvRMSE and NMBE). One approach is to look at the whole district as one aggregate building, while the other, introduced for the first time herein, consists in deriving the weighted-average of the error of each building. The main contribution of this study is to provide simultaneous calibration for multiple buildings in the same district—and subject to the same UHI intensity. Hence, the UHI intensity (urban-rural temperature/humidity differential) is estimated alongside other calibration parameters. For the weighted average approach, CvRMSE found is between 19.09% and 19.40%, while NMBE is between 16.24% and 16.39%. For the aggregated building, CvRMSE is between 2.71% and 4.04%, while NMBE is between 1.95% and 2.35%. [ABSTRACT FROM AUTHOR]

The interpretation of the energetic signature of a city, taken as an integrated urban energy system, has been attempted in this study. Instead of the customary bottom-up approach, we successfully identified an average gray-box dynamic model by inversion of measured hourly system load and weather data. The third-order lumped-parameter thermal network model is derived by applying energy conservation principles to major nodes representing buildings, paved surfaces and urban canopy. This powerful data-driven approach offers deep insights into the thermo-physical properties of the built structures as well as the coupling of buildings and the urban microclimate. In particular, the Urban Heat Island (UHI) intensity has been determined to be close to 2 °C while the corresponding electricity cooling load penalty is 12%. [ABSTRACT FROM AUTHOR]

The relationship between Urban Heat Island (UHI) and energy consumption in buildings has been widely observed and studied. The aim of this paper is to investigate the impact of large-scale deployment of indirect Vertical Greenery Systems (VGS) on the cooling demand of buildings and on the urban microclimate. VGS significantly reduces air temperature and wind speed near the walls. In doing so, it also positively impacts the UHI intensity. This is achieved mainly through the conversion of sensible heat to latent heat mediated by evaporation and transpiration from the VGS foliage. Evapotranspiration is a physically complex phenomenon and its interaction with the building and the urban climate is difficult to model accurately. We propose to use a dynamic nonlinear lumped parameter thermal network model to determine the thermal interactions between the prototypical building, the VGS, the paved road, the urban canopy air and the atmosphere. The model accounts for both sensible and latent exchanges within and outside the building. Solar (short-wave) radiation on building façade and road accounts for shading and unlimited diffuse reflections. Long-wave radiation among surfaces and between surfaces and the sky are estimated using view factors and the fully nonlinear Stefan-Bolzmann law. Building envelope infiltration rate and convective heat transfer coefficient vary with wind speed so as to properly reflect the energetic impact of wind speed attenuation near the wall due to the foliage. The thermal and aerodynamic characterization of the vegetation is based on the formulations proposed by Deardorff (1978). The evapotranspiration rate is estimated based on the Penman formula and is driven by the ‘vapor pressure deficit’ between actual vapor pressure in the ambient air and the saturation vapor pressure assumed to prevail on the surface of leaves. The calculation of sensible and latent heat fluxes between the urban canopy and the first level of the atmosphere considers buoyancy effects, using the coefficients introduced by Mascart et al. (1995). First, a base case model (no VGS) is created and validated using both building energy consumption data and urban air temperature measurements. The validated model is then used to investigate the impact of a large-scale deployment of VGS in the urban context. The weather data and the typical building thermo-physical properties are from the UAE. Comparison of the urban base case to the rural base case (both without VGS) shows a cooling load penalty, due to the UHI, of about 7 % . Retrofitting VGS to all buildings in the urban domain of study results in a 5 − 8 % reduction of the cooling load and a dramatic drop of the urban air temperature of about 0.7 − 0.9 °C, reducing the UHI intensity by almost half. [ABSTRACT FROM AUTHOR]

Over the last decade, significant efforts have been made to develop sophisticated physics-based urban simulators, given the undeniable need for sustainable-city initiatives to consider the potential impacts of climate change and massive urban growth. Nevertheless, even as a growing number of researchers have expanded their scope to the urban realm, there remain many problems resulting from the complexity of the urban microclimate, such as the Urban Heat Island (UHI) effect. This study is initiated with the intention to account for uncertainty in developing more coherent and integrated strategies concerning the energy and environmental issues in an urban system. The analysis builds upon the previously reported and updated Urban Weather Generator (UWG) to present a deep look into an existing urban microclimate system in Abu Dhabi (UAE). The case-specific baseline information is generated for the UWG and a global regression-based sensitivity analysis using the Monte Carlo technique is performed. Based on 30 candidate inputs covering the meteorological factors, urban characteristics, vegetation variables, and building systems, the uncertainty analysis indicates that the UWG is a fairly robust simulator to approximate the urban thermal behavior in downtown Abu Dhabi for different seasons. The identified significant factors will be the subject of future research to gain a higher resolution of critical urban simulation inputs, thereby providing more informed domain knowledge of the underlying mechanisms driving the microclimatic effect on the energy and environmental performances. [ABSTRACT FROM AUTHOR]

In this paper, we provide further evidence of the reliability of a lumped parameter urban canopy model coupled with an EnergyPlus building energy model to estimate urban temperatures. In a previous paper, we presented a preliminary validation of the model using data measured at Masdar Institute, Abu Dhabi, United Arab Emirates. At present, we conduct a more comprehensive validation based on BUBBLE experimental data measured in the Sperrstrasse, a street canyon located in Basel downtown, Switzerland. To extend the coupled scheme for the Sperrstrasse and future work, we developed methods for approximating waste heat releases generated by a heating system, anthropogenic heat gains created by traffic, and direct normal solar irradiance. Based on a baseline coupled scheme model for the Sperrstrasse, we evaluate the sensitivity of urban temperature estimates to ±20% variations of each parameter. We finally show, through Monte-Carlo analysis, that the coupled scheme can achieve satisfactory accuracy in a dense Central European city. [ABSTRACT FROM AUTHOR]

In this study, we present a meso-scale simulation of the urban microclimate in Berlin, Germany, using the Weather Research and Forecasting (WRF) numerical weather prediction platform. The objective of the study is to derive an accurate estimate of the near-surface urban heat island (UHI) intensity. The simulation is conducted over a two-week summer period. We compare different physical schemes, different urban canopy schemes and different methods for estimating the UHI intensity. The urban fraction of each urban category is derived using the Copernicus Impervious Density data and the Corine Land Cover data. High-resolution City Geography Markup Language (CityGML) data is used to estimate the building height densities required by the multi-layer urban canopy model (UCM). Within the single-layer UCM, we implement an anthropogenic heat profile based on the large scale urban consumption of energy (LUCY) model. The optimal model configuration combines the WRF Single Moment Five-Class (WSM5) microphysics scheme, the Bougeault–Lacarrère planetary boundary layer scheme, the eta similarity (Mellor–Yamada–Janjic) surface layer scheme, the Noah Multi-Parameterization land surface model, the Dudhia and Rapid Radiative Transfer Model (RRTM) radiation schemes, and the multi-layer UCM (including the building energy model). Our simulated UHI intensity results agree well with measurements with a root mean squared error of 0.86 K and a mean bias error of 0.20 K. After model validation, we proceed to compare several UHI intensity calculation methods, including the 'ring rural reference' (RRR) method and the 'virtual rural reference' (VRR) method. The VRR mthod is also known as the 'urban increment' method. We suggest and argument that the VRR approach is superior. [ABSTRACT FROM AUTHOR]

Villas are a very common building typology in Abu Dhabi. Due to its preponderance in residential areas, studying how to effectively reduce energy demand for this type of building is critical for Abu Dhabi, and many similar cities in the region. This study aims to show the impact of proposed energy efficiency measures on a villa using a calibrated model and to demonstrate that to be accurate, the model must be driven using urban weather data instead of rural weather data due to the significance of the urban heat island effect. Available data for this case study includes construction properties, on-site (urban) weather data, occupancy-related loads and schedules and rural weather data. Four main steps were followed, weather data customisation combining urban and rural weather variables, model calibration using a genetic algorithm-based tool and simulating retrofit strategies. We created a calibrated model for electricity demand during 2016–2017 with a 4% normalized mean bias error and an 11% coefficient of variation of the mean square error. Changing from none to all retrofit strategies results in a 34% reduction in annual energy consumption. According to the calibrated model, increased urban temperatures cause a 7.1% increase in total energy consumption. [ABSTRACT FROM AUTHOR]