An Urban Energy Baseline Model for Measurement & Verification of Building Energy Efficiency Retrofits in Abu-Dhabi

Abstract

Increasing awareness of climate change, pollution, reduced infrastructure investment availability and escalating fossil fuel prices have set pressure over policymakers and energy sector planners to better utilize the electricity infrastructure by reducing or shifting peak load and to conserve energy. Demand Side Management (DSM) measures ranging from advanced building controls to indoor-climate control and building equipment/envelope enhancement are designed to address this problem. Accurate determination of the ex-post impact of such measures is a widely recognized barrier to the wider deployment of DSM initiatives. The task is complicated by the dynamic nature of the system, the coupled interaction of multiple sub-systems and the high correlation with weather and other perturbations. A baseline model of electricity consumption was establish for the city of Abu Dhabi, UAE, which will enable the comparison between different DSM interventions focused on curbing cooling demand and the business-as-usual (baseline) case. In the procedure proposed, also referred to as inverse load modeling, a novel hourly regression model of the aggregate load was estimated based on historical data. Different day schedules and seasonalities were accounted for, as well as the effect of weather variables such as temperature, relative humidity, wind speed and solar irradiance. The model produced accurate results; adjusted R-squared of 0.9931 for the training data (year 2010). The load during the first half of 2011 was used as verification data-set resulting in a RMSE of 35.63MW, equivalent to 1.84% of the annual peak load, and a MAPE of 2.64%. Based on the model, the weather dependent load account for approximately 30% of the overall electricity usage, while during the peak summer hour this value reaches 49% of the total electricity load. This information was combined with Urban Planning Council's typical building models for Abu-Dhabi in order to estimate the overall load due to cooling. The overall electricity consumption for cooling reaches 57% of the total load for the year, while it is estimated in 75% for the year's peak load hour. These values are to be minimized with policies and building codes that target overall energy efficiency, in order to curb emissions and wasteful energy consumption.

Date of Award	Jun 2013
Original language	American English
Supervisor	Afshin Afshari (Supervisor)