Team Leader
irfan Ullah
Texas A&M University
Electrical and Computer Engineering
irfan@tamu.edu
Project Type
Research
Who Can Join
Undergraduate Students
Project Description
Project 1 : Load Data Processing and DER Profile Generation
This project involves collecting and preprocessing load data from the distribution network, modeling uncertainty in load demand, and generating synthetic distributed energy resource (DER) profiles such as photovoltaic generation and battery storage. The outputs will serve as the basis for system-level performance evaluation under uncertain conditions.
Project 2 : Visualization and Comparative Analysis of DER Performance
This project focuses on creating clear and informative visualizations for load profiles, distributed energy resource (DER) profiles, and comparative plots such as load vs. PV output and load vs. PV + battery output. Uncertainty bands will be overlaid on load plots, and regions of met or unmet demand will be highlighted to assess DER effectiveness under various scenarios.
Project 3 : Optimal Power Flow Analysis for Post-Restoration Scenarios
This project applies optimal power flow (OPF) analysis to a restored distribution network. Tasks include updating the network model with restoration results, running OPF simulations, analyzing system behavior post-restoration, and comparing OPF outcomes with target restoration plans to evaluate performance and identify potential improvements.
Team Needs
Project 1 – Load Data Processing and DER Profile Generation
Requirements: Basic understanding of power distribution systems
Skills: Basic Python programming, and familiarity with CSV or Excel data handling.
Motivation: Interest in working with real-world energy data and learning how to model load uncertainty and renewable generation profiles.
Project 2 – Visualization and Comparative Analysis of DER Performance
Requirements: Basic understanding of power distribution systems
Skills: Basic data visualization skills (e.g., using Python’s or Excel charts) and comfort interpreting graphs.
Motivation : Enthusiasm for transforming raw technical data into clear and compelling visual stories that highlight system performance, identify trends, and reveal insights for decision-making. An interest in using visualization to bridge the gap between complex power system analysis and practical understanding.
Project 3 – Optimal Power Flow Analysis for Post-Restoration Scenarios
Requirements: Basic understanding of power distribution systems, math
Skills/Experience Needed: programming, interest in learning optimization methods, and ability to interpret simulation results.
Motivation: Interest in learning how decisions made in operating a power distribution system can change its performance and efficiency. Excited to use programming and simple optimization tools to see how different choices affect the network, and to explore ways to make the system run better.
Special Opportunities
This project provides undergraduate students with the opportunity to develop valuable skills in Python and programming skills, OpenDSS simulation, and power system analysis while working as part of a collaborative team. Team members will engage in data processing, visualization, and optimization tasks that mirror real-world challenges in the energy industry. They will also gain experience in team-based problem solving, technical reporting, and presenting results, which are key skills for both professional and academic settings. Participants will build practical skills that are highly valued in both industry and academic research, gaining hands-on exposure to research methods and tools. This experience will prepare students for future roles in the power and energy sector as well as competitive opportunities in graduate school and research assistant positions.