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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Lunchtime Seminar Series Presents Dr. Tyler Frazier, AICP from Technische Universitat, Berlin, Dept. of Transportation System Planning and Telematics for a talk on:Powering Accra: Using agent-based land use simulation to project electricity demand for Ghana’s Capital City.
The primary research objective of this work was to create an agent-based urban simulation based on land use at the plot level for projecting the disaggregated electricity demand of the Greater Accra Metropolitan Area (GAMA). A simulation system comprised of location choice,regression, and simple models was used to project household, employment andland development decisions. Households, persons, and jobs tables were synthetically generated from the Ghana Living Standards Survey 2005 (GLSS5) data and incorporated for use in the Open Platform for Urban Simulation (OPUS). Electricity demand was projected for each of the simulation years based on a generalized0 linear regression. Numerous geospatial datasets were projected and edited in ArcGIS, which describe the physical composition of Accra in its totality, including buildings, roads and electricity infrastructure. Household mobility was estimated from a modified Cox Regression of residential mobility in Accra (Bertrand et al.) and applied to the GLSS5 for use in the location choice model, while employment coefficients and parameters describing land value were derived from literature (Buckley et al.). This agent-based urban simulation has been successfully applied for projecting the electricity demand of the Korle Bu district for the time period 2006 until 2025, based on monthly electricity consumption per meter.
