Decision Support Tool Based on a City-Scale Grey-Box Model for Energy Efficiency Retrofit Impact Assessment in Abu Dhabi

Abstract

Based on previous work, a linear regression model of electricity consumption for the city of Abu Dhabi, UAE was built, which enables the extraction of cooling load from the total electricity consumption. Different seasonalities, as well as marginal effect of weather parameters, such as temperature, relative humidity, wind speed, and solar irradiance were taken into account in constructing this model. Afterwards, an urban canopy and building energy model based on a thermal network of constant resistances and capacitances was established with the cooling load extracted as one of its input. The RC model represents the underlying energy interactions between buildings and their urban environment. The main advantage of the model is that the parameters obtained have physical meanings, which enables the comparison between different DSM interventions on curbing cooling demand and the business-as-usual case. Another advantage is the simplicity of the model and its computational efficiency, which makes it possible to easily evaluate different hypotheses and parameter sensitivities. The model is then used to investigate the Urban Heat Island (UHI) effect, its impact on energy consumption, and ways to attenuate it. It is found that the cooling load accounts for approximately 60% of the total electricity consumption and it reaches approximately 70% during the peak hours in summer. In addition, UNI intensity, which is the average temperature difference inside and outside the urban canyon is between 2 to 3_C and is estimated that a significant portion of the cooling load merely compensates the UHI effect. The methods and conclusions obtained in this study can be applied to a wide range of energy modeling and urban studies.

Date of Award	May 2014
Original language	American English
Supervisor	Afshin Afshari (Supervisor)