MID-TERM FORECASTING MODEL OF ABU-DHABI’S ELECTRICITY CONSUMPTION APPLIED TO DEMAND-SIDE MANAGEMENT IMPACT ASSESSMENT

摘要

Climate change, pollution, reduced infrastructure investmentrnavailability and escalating fossil fuel prices havernresulted in renewed emphasis on energy conservation andrnefficient electricity infrastructure utilization through DemandrnSide Management (DSM) in the existing buildingrnstock. DSM measures ranging from enhanced buildingrncontrols to equipment/envelope retrofits are designed tornaddress this problem. The difficulty to accurately assessrnthe ex-post impact of such measures is a widely recognizedrnbarrier to the wider deployment of DSM. The task isrncomplicated by the dynamic nature of the energy consumingrnprocesses, the coupled interaction of multiple subsystemsrnand the high correlation of demand with weatherrnand other perturbations. An hourly regression-based modelrnof the load, driven by exogenous variables is proposedrnto address this problem. The model was estimated for therncity of Abu Dhabi, UAE, using measured data from pre-rnDSM period. It was then used to profile the “baseline”rnenergy consumption over a selected post-DSM periodrnrevealing, though comparison with the actual energy consumption,rnthe savings attributable to the DSM intervention.rnThe model produced accurate results; adjusted Rsquaredrnof 0.9931 (training period - year 2010), a RMSErnequivalent to 1.84% of the annual peak load, and a MAPErnof 2.64% (verification data-set first-half 2011).