This study presents the preliminary design and performance assessment of a 12-MW utility-scale photovoltaic (PV) solar power plant proposed for Hebbronville, Texas. The site was selected due to its high solar irradiance, land availability, and proximity to existing electrical infrastructure. Solar resource data obtained primarily from the NREL database, using two years of solar data, is used to evaluate system performance. The study analyzes plant layout, PV module and inverter selection, and the use of fixed-tilt and tracking panel configurations. Using photovoltaic performance factors (POFs) and standard generation calculations, the plant’s expected power generation and annual energy production are estimated to evaluate the anticipated performance of the system.

This project designs a 15-MW photovoltaic (PV) power plant, located just outside San Angelo, TX in San Saba County, Texas (30.98∘N, −99.00∘W), to evaluate the performance trade-offs between two configurations: a fixed-tilt stationary system and a horizontal single-axis tracking (HSAT) system. Utilizing three years of meteorological data (2021–2023) from the NREL National Solar Radiation Database, the study will perform parametric analyses on the Ground Coverage Ratio (GCR) and DC:AC loading ratios. Calculations will determine annual energy yield, Performance Ratio (PR), and Levelized Cost of Energy (LCOE). Results will quantify the energy gain of tracking systems against increased land requirements and O&M costs, providing a technical justification for solar deployment in the Texas CREZ corridor

This poster presents the electrical and controls design of the Automated Parts Washer (APW), a senior capstone sponsored by Mary Kay and developed by engineering students at Texas Christian University. The system will integrate sensors, actuators, and a programmable control architecture to automate the washing cycle while minimizing operator intervention, designed to improve efficiency, safety, and consistency in industrial component cleaning.. A PLC control system coordinates key subsystems including fluid pumps, spray nozzles, and heating elements, and an ultrasonic bath component to ensure uniform cleaning coverage. Electrical design emphasizes safe power distribution, component protection, and reliable signal interfacing between sensors and control hardware. Control logic will be implemented to manage cycle timing, temperature regulation, and fluid circulation while incorporating safety interlocks and fault detection. Human-machine interaction is provided through a user interface that allows operators to select wash cycles and monitor system status. The resulting design demonstrates how integrated electrical systems and control strategies can transform a traditionally manual cleaning process into a repeatable, automated solution suitable for small-scale manufacturing and maintenance environments.

Climate change and economic factors have led to a considerable increase in demand for renewable power generation in Texas, with yearly renewable generation increasing from 12% in 2015 to 34% in 2025. This study evaluates the feasibility of a 100 MW wind power plant located on the outskirts of El Paso, TX. The plant would require 30 to 40 wind turbines producing 3 MW each, powering up to 75,000 homes on average and providing clean, independent energy to the surrounding metropolitan area. The report focuses on the technical concerns of the proposed wind power plant and predicts its performance based on average hourly weather data in the region.

Due to unprecedented urbanization in North Texas, coyotes have become more frequently observed in urban settings. The proposed project will examine the spatial distribution of coyote observations in North Texas, focusing on identifying spatial patterns. It also assesses whether these patterns are indicators of long-term adaptation in response to rapid urbanization in the region.  This study will use spatial analysis techniques to determine whether coyote observations are spatially clustered, identify potential hotspots, and assess whether the clustering is associated with a certain cover type. In addition, visual comparisons of multitemporal observations of data will be conducted to evaluate whether distribution patterns change over time. By integrating hotspot analysis and land cover data, the project aims to better understand how coyotes may be adapting to urban environments in North Texas.