Search

A pre-requisite to reducing the energy intensity of the building sector is to assess and understand current drivers of energy consumption. Drivers include building design characteristics, outdoor environmental conditions, as well as the operation patterns of building systems by facility managers and occupants. In the United Arab Emirates (UAE), where buildings consume more than 70% of the total electricity generated, a comprehensive analysis of the drivers of building energy performance has not yet been conducted. This paper proposes an empirical top-down statistical framework to comprehensively evaluate drivers of energy use for a stock of buildings. The approach is unique in its ability to capture the combined effects of technical, as well as, operation-related building parameters. A combination of data analysis techniques, including CHAID decision trees and regression models, is proposed and applied to data gathered from 713 mixed-use buildings in downtown Abu Dhabi. Results indicate that in addition to physical building parameters such as window tinting, operational parameters, including AC cleanliness, chiller condition, and thermostat temperature setting have shown significant impacts on energy consumption levels. The findings shed light on the crucial – yet often overlooked – role of facility managers and occupants in ensuring efficient energy performance in the building sector. [ABSTRACT FROM AUTHOR]

• Standalone urban energy/climate model forced by ERA5 atmospheric data. • Modeling concept based on the physical network principle and implemented in a graphical development/simulation environment. • Computationally light numerical model can be incorporated in design optimization. • District cooling is best design option in terms of both UHI mitigation and energy demand conservation. Standalone urban canopy models attempt to replace the full-fledged atmospheric representation with a simplified equivalent. In this study, we investigate the offline forcing of an offline Standalone Urban Energy/Climate Model (SUECM) by the fifth generation reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5). The result is a computationally light numerical model of the urban canopy air that can be incorporated in a design optimization work flow. The model is applied to the city of Abu Dhabi (United Arab Emirates). The model's accuracy is validated against measurements. The urban heat island (UHI) mitigation and building energy conservation potential of several urban design/retrofit scenarios is evaluated in comparison to business-as-usual. District cooling implementation is best overall with an estimated reduction of cooling electricity demand by more than 40% and of UHI intensity by more than 25%. Building-integrated vegetation systems (green roof/wall) are also effective mitigation/conservation measures; however, their positive impact must be weighed against the need for irrigation. Among the two other design/retrofit scenarios, cool surfaces are more effective in reducing UHI (−16%) while energy efficient buildings are to be preferred in case cooling energy demand reduction is prioritized (−25%). Based on the physical network representation principle, the model has been implemented in a graphical development and simulation environment, thereby simplifying specializations and future enhancements. [ABSTRACT FROM AUTHOR]