This website is best viewed in a browser that supports web standards.

Skip to content or, if you would rather, Skip to navigation.

Northwest Missouri State University


Library Home » Electronic Theses » Geographic Information Science » Chad Benham

A GIS Based Decision and Suitability Model: Solving the "Tower Location Problem" in Support of Electric Power Grid Initiatives

Author: Chad Benham
M.S. in Geographic Information Science
Department of Humanities and Social Science
June 2012
Download Files
Full Text (PDF, 3.8MB)
Abstract

Georgia Power Company (GPC) is in the midst of improving its electrical power grid by upgrading equipment in the field. It is working towards building a version of the "Smart Grid", a more efficient, secure, and environmentally sound way of providing electricity to the State of Georgia. A big part of this effort is focused on replacing mechanical power meters at commercial and residential customers with Automated Metering Infrastructure (AMI) power meters which can communicate power usage information back to the company wirelessly. These AMI meters rely on radio frequency communication channels similar to broadband and WiFi to send signals wirelessly back to a communication tower which collects then forwards the data to an operating center.

In most parts of central and southern Georgia these communication towers are widespread and can easily receive a signal from the meters. The northern parts of Georgia present a challenge to the transmission of radio signals. Mountains, valleys and other topographically varied features hinder the transmission of signals sent in the portion of the electromagnetic spectrum in which the AMI meters operate. Finding ways to get a signal from the meter back to a communication tower becomes a spatial problem involving line-of-sight between the meter and tower, and occasionally there is a need to build new towers to handle the AMI meter demand.

A suitability model was built that took land features along with other data inputs to help narrow down potential building sites for new radio communication towers. The main variables taken into account by this model were elevation, slope, the distance between one tower to the next, and the distance between the meters and each tower. After the model identified appropriate sites for building a tower, additional location-allocation methods were employed which further reduced the potential tower construction sites to the most optimal locations.

This model was tested in one of the most rugged and mountainous sections of the State of Georgia, and it produced enough tower locations so that all the AMI meters under study were able to "see" a communication tower and send a radio signal. This model should be helpful in reducing the research expenditures of GPC by narrowing down the possible locations the company will look at when new communication towers are needed.