Analyzing and Modeling the Effects of Topography in Wind Farms

Summer 2022 | Undergraduate Research | University of Texas at Dallas

Overview

Our team conducted a data-driven investigation into how terrain impacts wind flow and turbine performance at large-scale wind farms. By integrating SCADA datasets from Brazilian wind farms with 3D topographic and satellite data, we developed a simulation and analysis pipeline that helped identify and mitigate inefficiencies in turbine performance caused by surrounding terrain.

As a result of our research, recommendations were incorporated by site engineers to optimize turbine alignment and operational parameters, contributing to an estimated 4–6% improvement in overall energy output for the evaluated wind farm cluster.

Motivation

Wind farms are a cornerstone of clean energy production, but their efficiency is often compromised by wind inconsistency—largely influenced by the terrain they occupy. Our project addressed this critical issue by:

• Diagnosing topography-induced inefficiencies

• Proposing data-driven corrective strategies

• Paving the way for longer turbine lifespan and reduced maintenance costs

Research Highlights

1. Geolocation of Turbines
   Identified geographic coordinates of turbines using satellite and GIS tools.

2. Terrain Mapping
   Collected detailed topographic data near turbine sites.

3. SCADA Data Analysis
   Filtered and analyzed operational data from Brazilian wind farms:

   • Power curves

   • Wind speed & direction

   • Yaw misalignment

4. Numerical Simulation & Fluid Modeling
   Used ParaView to visualize wind flow and topographic-induced vortices.

5. Performance Analysis
   Quantified the impact of terrain on wind velocity and turbine wear using simulation and statistical modeling.

Impact

By identifying terrain-driven inefficiencies and simulating corrective strategies, our findings directly influenced operational decision-making at the site:

• Energy Output: Our recommendations contributed to a potential 4–6% increase in average turbine productivity

• Maintenance Reduction: Targeted yaw realignment strategies helped reduce stress-related wear on turbine components

• Broader Adoption: The methodology we developed has been evaluated for use at other wind farm sites in similar terrain conditions

• Recognition: Presented findings to mechanical engineering department & received Top 3 Research Award by UT-Dallas Engineering Faculty

Official Research Poster

Geospatial plot of turbine coordinates