Student Success: Master’s Thesis Completed!
We are thrilled to congratulate Aaron Jones, Anish Ravichandran, and Nirmal Bhatt on the successful completion of their master's theses!
Each of them has made remarkable contributions to the electric energy systems field, and we couldn't be prouder of their achievements.
Anish and Nirmal are now embarking on exciting careers in industry, and we wish them all the best in their future endeavors. Aaron will continue his academic journey as he pursues a PhD, and we can’t wait to see what incredible work he will accomplish.
Congratulations to all three of you - your achievements make us proud!
Anish Ravichandran
Title: “Toward An Explainable Electric Power Grid Operation
Assistant Using Large Language Models”
Abstract: This research investigates how Large Language Models (LLMs) can assist grid operators in managing the increasing complexity of power systems driven by electrification and renewable integration. By developing and testing LLM agents on grid operation benchmarks, the thesis evaluates their ability to provide actionable insights and support decision-making in both steady-state and failure scenarios. While challenges remain in tool integration and operational consistency, this work highlights the potential of LLMs to enhance grid resilience and sustainability.
Aaron Jones
Title: “Modeling and Analysis of Voltage Feasibility Problems for Cost-Effective Microgrids”
Abstract: This research addresses the integration of renewable energy resources into the grid, focusing on modeling techniques to analyze the feasibility of microgrid topologies. Microgrids enable flexible, efficient integration of distributed energy resources (DERs) like photovoltaic (PV) systems, supporting sustainable grid design. Using data from an Illinois-based microgrid, this study evaluates the feasibility of increasing PV units grid support capabilities while maintaining voltage within constraints. Simulations with Alternating Current Optimal Power Flow (AC-OPF) reveal the limits of reactive power support from PV systems, showing voltage collapse beyond certain thresholds. Optimization ensures feasible solutions, highlighting the importance of AC-OPF for reactive power management. Future research will address challenges like dynamic voltage instability and inverter control complexities in high PV-penetration microgrids.
Nirmal Bhatt
Title of thesis: “The Missing Megawatts Problem: Improving Modeling Practices to Prepare for an Uncertain Future”
Abstract: Long-term energy system planning is one of the most pressing challenges for the power sector, which must maintain reliability while decarbonizing. Currently, no unified regulatory, modelling, or market framework exists in the United States to facilitate planning in pursuit of a clean and reliable grid. Variable renewable energy (VRE) generation can produce cheap power but they increase the grids exposure to interannual variability in demand and VRE generation. This raises questions about how grid planners will value VRE and clean firm power (such as nuclear power). This thesis evaluates the importance of considering interannual variability and clean firm power in long-term energy system planning. I use GenX, an open-source capacity expansion model, to model the U.S. New England region in 2050 assuming a high degree of electrification and various technology availability and emissions reduction pathways. I find that clean firm power will reduce the cost of decarbonizing the New England grid but that grid planners must consider decades of weather and demand data if they are to make appropriate investments. I also present a novel outputs-based timeseries clustering method which allows models like GenX to optimize grids using longer timeseries of weather and demand data. Based on my work, I recommend that policymakers, grid operators, and market designers establish rigorous standards around energy modelling for long-term planning that includes multiple scenarios and appropriately values technologies such as firm power.