8 citations · 18 across the 28 of their papers we have counts for
30 papers
Congestion Structure and Exceedance Bounds for Locational Marginal Emissions
Cameron Khanpour, Samuel Talkington, Daniel K. Molzahn
Locational marginal emissions (LMEs) give the sensitivity of total operating carbon emissions to nodal power demand. We show that this vector with entries has a much smaller in…
Grid Trouble in Paradise: Uncovering Vulnerable Distributed Energy Resources and Their Grid-Level Risks
Anna Raymaker, Samuel Talkington, Zeezoo Ryu +8
Grid-connected solar distributed energy resources (DERs), such as solar inverters and monitoring platforms, have been deployed at unprecedented scale over the past few years, with…
Targeted Power System Frequency Attack via the Selection of Maliciously Controlled Inverters
Xiangyu Zou, Betelihem Ashebo, Daniel K. Molzahn
This paper studies how an adversary can execute a power system frequency attack by choosing the most effective subset of inverter-based resources (IBRs) as malicious control nodes.…
Zero-Sum Power Factor Games
Cameron Khanpour, Samuel Talkington, Mathieu Dahan +1
Variable active power injections arising from device behavior or compromised dispatch complicate voltage regulation in electric power networks with distributed energy resources (DE…
Ramping-aware Enhanced Flexibility Aggregation of Distributed Generation with Energy Storage in Power Distribution Networks
Hyeongon Park, Daniel K. Molzahn, Rahul K. Gupta
Power distribution networks are increasingly hosting controllable and flexible distributed energy resources (DERs) that, when aggregated, can provide ancillary support to transmiss…
Efficient Network Reconfiguration by Randomized Switching
Samuel Talkington, Dmitrii M. Ostrovskii, Daniel K. Molzahn
We present an algorithm that efficiently computes nearly-optimal solutions to a class of combinatorial reconfiguration problems on weighted, undirected graphs. Inspired by societal…
Fair Cost Allocation in Energy Communities: A DLMP-based Bilevel Optimization with a Shapley Value Approach
Hyeongon Park, Kyuhyeong Kwag, Daniel K. Molzahn +1
Energy communities (ECs) are emerging as a promising decentralized model for managing cooperative distributed energy resources (DERs). As these communities expand and their operati…
Differentiating Through Power Flow Solutions for Admittance and Topology Control
Samuel Talkington, Daniel Turizo, Sergio A. Dorado-Rojas +2
The power flow equations relate bus voltage phasors to power injections via the network admittance matrix. These equations are central to the key operational and protection functio…
Machine Learning Guided Optimal Transmission Switching to Mitigate Wildfire Ignition Risk
Weimin Huang, Ryan Piansky, Bistra Dilkina +1
To mitigate acute wildfire ignition risks, utilities de-energize power lines in high-risk areas. The Optimal Power Shutoff (OPS) problem optimizes line energization statuses to man…
Admittance Matrix Concentration Inequalities for Understanding Uncertain Power Networks
Samuel Talkington, Cameron Khanpour, Rahul K. Gupta +5
This paper presents conservative probabilistic bounds for the spectrum of the admittance matrix and classical linear power flow models under uncertain network parameters; for examp…
Certifying the Nonexistence of Feasible Path Between Power System Operating Points
Mohammad Rasoul Narimani, Katherine R. Davis, Daniel K. Molzahn
By providing the optimal operating point that satisfies both the power flow equations and engineering limits, the optimal power flow (OPF) problem is central to power systems opera…
Error Bounds for Radial Network Topology Learning from Quantized Measurements
Samuel Talkington, Aditya Rangarajan, Pedro A. de Alcântara +3
We probabilistically bound the error of a solution to a radial network topology learning problem where both connectivity and line parameters are estimated. In our model, data error…
VArsity: Can Large Language Models Keep Power Engineering Students in Phase?
Samuel Talkington, Daniel K. Molzahn
This paper provides an educational case study regarding our experience in deploying ChatGPT Large Language Models (LLMs) in the Spring 2025 and Fall 2023 offerings of ECE 4320: Pow…
Optimizing Battery and Line Undergrounding Investments for Transmission Systems under Wildfire Risk Scenarios: A Benders Decomposition Approach
Ryan Piansky, Rahul K. Gupta, Daniel K. Molzahn
With electric power infrastructure posing an increasing risk of igniting wildfires under continuing climate change, utilities are frequently de-energizing power lines to mitigate w…
Evaluating Undergrounding Decisions for Wildfire Ignition Risk Mitigation across Multiple Hazards
Ryan Piansky, Daniel K. Molzahn, Nicole D. Jackson +1
With electric power infrastructure increasingly susceptible to impacts from climate-driven natural disasters, there is an increasing need for optimization algorithms that determine…
Sample-Based Piecewise Linear Power Flow Approximations Using Second-Order Sensitivities
Paprapee Buason, Sidhant Misra, Daniel K. Molzahn
The inherent nonlinearity of the power flow equations poses significant challenges in accurately modeling power systems, particularly when employing linearized approximations. Alth…
Optimizing Phase Allocation in Unbalanced Power Distribution Networks using a Linearized DistFlow Formulation
Rahul K. Gupta, Daniel K. Molzahn
Power distribution networks, especially in North America, are often unbalanced but are designed to keep unbalance levels within the limits specified by IEEE, IEC, and NEMA standard…
AC-Informed DC Optimal Transmission Switching Problems via Parameter Optimization
Babak Taheri, Daniel K. Molzahn
Optimal Transmission Switching (OTS) problems minimize operational costs while treating both the transmission line energization statuses and generator setpoints as decision variabl…
Strategic Electric Distribution Network Sensing via Spectral Bandits
Samuel Talkington, Rahul Gupta, Richard Asiamah +2
Despite their wide-scale deployment and ability to make accurate high-frequency voltage measurements, communication network limitations have largely precluded the use of smart mete…
Improving the Accuracy of DC Optimal Power Flow Formulations via Parameter Optimization
Babak Taheri, Daniel K. Molzahn
DC Optimal Power Flow (DC-OPF) problems optimize the generators' active power setpoints while satisfying constraints based on the DC power flow linearization. The computational tra…
Beyond Algorithmic Fairness: A Guide to Develop and Deploy Ethical AI-Enabled Decision-Support Tools
Rosemarie Santa Gonzalez, Ryan Piansky, Sue M Bae +2
The integration of artificial intelligence (AI) and optimization hold substantial promise for improving the efficiency, reliability, and resilience of engineered systems. Due to th…
Quantifying Metrics for Wildfire Ignition Risk from Geographic Data in Power Shutoff Decision-Making
Ryan Piansky, Sofia Taylor, Noah Rhodes +3
Faults on power lines and other electric equipment are known to cause wildfire ignitions. To mitigate the threat of wildfire ignitions from electric power infrastructure, many util…
Discrete Shortest Paths in Optimal Power Flow Feasible Regions
Daniel Turizo, Diego Cifuentes, Anton Leykin +1
Optimal power flow (OPF) is a critical optimization problem for power systems to operate at points where cost or other operational objectives are optimized. Due to the non-convexit…
Long Duration Battery Sizing, Siting, and Operation Under Wildfire Risk Using Progressive Hedging
Ryan Piansky, Georgia Stinchfield, Alyssa Kody +2
Battery sizing and siting problems are computationally challenging due to the need to make long-term planning decisions that are cognizant of short-term operational decisions. This…