alexa Electricity Demand Evolution Driven by Storm Motivated
ISSN: 2167-0587

Journal of Geography & Natural Disasters
Open Access

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Research Article

Electricity Demand Evolution Driven by Storm Motivated Population Movement

Melissa R Allen1,2, Steven J Fernandez1,2*, Joshua S Fu1,2 and Kimberly A Walker3

1University of Tennessee, Knoxville, Oak Ridge, USA

2Oak Ridge National Laboratory, Oak Ridge, USA

3Indiana University, Oak Ridge, USA

*Corresponding Author:
Steven J Fernandez
Oak Ridge National Laboratory
Oak Ridge, USA
Tel: 865 576-3565
E-mail: [email protected]

Received Date: June 04, 2014; Accepted Date: June 26, 2014; Published Date: July 07, 2014

Citation: Allen MR, Fernandez SJ, Fu JS, Walker KA (2014) Electricity Demand Evolution Driven by Storm Motivated Population Movement. J Geogr Nat Disast 4:126. doi: 10.4172/2167-0587.1000126

Copyright: © 2014 Allen MR, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

Managing the risks to reliable delivery of energy to vulnerable populations posed by local effects of climate change on energy production and delivery is a challenge for communities worldwide. Climate effects such as sea level rise, increased frequency and intensity of natural disasters, force populations to move locations. These moves result in changing geographic patterns of demand for infrastructure services. Thus, infrastructures will evolve to accommodate new load centers while some parts of the network are underused, and these changes will create emerging vulnerabilities. Forecasting the location of these vulnerabilities by combining climate predictions and agent based population movement models shows promise for defining these future population distributions and changes in coastal infrastructure configurations. In this work, we created a prototype agent based population distribution model and developed a methodology to establish utility functions that provide insight about new infrastructure vulnerabilities that might result from these new electric power topologies. Combining climate and weather data, engineering algorithms and social theory, we use the new Department of Energy (DOE) Connected Infrastructure Dynamics Models (CIDM) to examine electricity demand response to increased temperatures, population relocation in response to extreme cyclonic events, consequent net population changes and new regional patterns in electricity demand. This work suggests that the importance of established evacuation routes that move large populations repeatedly through convergence points as an indicator may be under recognized.

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