Frazier, Tyler James: Powering Accra: Projecting Electricity Demand for Ghana‘s Capital City. - Bonn, 2011. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc:
author = {{Tyler James Frazier}},
title = {Powering Accra: Projecting Electricity Demand for Ghana‘s Capital City},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2011,
month = aug,

note = {The purpose of this research 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 were used to project household, employment and land development decisions. Households, persons, and jobs tables were synthetically generated from GLSS5 (Ghana Living Standards Survey 2005) data using Stata, built in a MySQL database 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 regression model. 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.). The model has been applied for projecting the electricity demand of the Korle Bu district in terms of high, medium and low economic and population growth rates for the time period 2006 until 2025, based on monthly electricity consumption per meter. An additional phase of this research envisions including all 12 GAMA districts (using data which has been obtained); infrastructure models to project demand for transportation, water & sewer, and solid waste facilities; as well as comparing weak and strong sustainability scenarios with the business-as-usual development path for cost-benefit analysis of proposed public policies.},
url = {}

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