1. Evaluating Wind Turbine Placement using Geographic Information Systems (GIS) Tools Manuel Silva Jr, Graduate Mentor: Francisco Haces, Faculty Advisor: Dr. David Ramirez, Funded by the National Science Foundation Texas A&M University Kingsville Chevy Chase Dr., Dallas, TX, 75006, United States
Abstract
Wind Farms are being increasingly utilized to produce clean energy. The state of Texas offers many wind regions optimal for harnessing wind energy. It is therefore important to identify the suitability of a specific region for wind turbine placement. Geographic Information Systems have the tools needed to analyze arrays of data layers which can determine the degree of optimality for such placement with regards to energy demands.
1. Introduction
Wind energy has generated a small portion of electricity compared to other forms but has continued to grow since 2015.This form of energy generation energy has increased since when observing that the number of turbines increased from 8,000 to 12,000.
2. Methodology
The objective was reached by combining databases through a GIS system that contained relevant data such as the Digital Obstacle File (DOF) form the Federal Aviation Administration (FAA) and the United States Geological Survey (USGS). Other useful sources of data were the National Renewable Energy Laboratory’s (NREL) Wind Data for the State of Texas, U.S Energy Information Administration’s (EIA) Electricity sales and USGS cities' population data. Distance Analysis were made from each county to wind turbine locations in the state. Emphasis was given to counties with larger population and power consumption.
3. Results and Conclusion
A large percentage of the turbines might be far away from the largest cities but they are in optimal wind zones. GIS proved to be a valuable tool to combine data from different sources and analyze it. This method could be applied to various other topics especially renewable energy such as the case with solar energy where extensive data exists.
Fig. 1- Texas wind regions according to NREL
Fig. 2- USGS and FAA turbine locations
Fig. 3 - Electricity consumption by county
Fig. 4- Counties to wind turbines distance analysis
Fig. 5- Turbine distribution
Fig. 6- Turbine distribution
Fig. 7- Turbine distribution
Proceedings of the 2018 ASEE Gulf-Southwest Section Annual Conference The University of Texas at Austin
April 4-6, 2018