20 papers
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…
Conservative Bias Linear Power Flow Approximations: Application to Unit Commitment
Paprapee Buason, Sidhant Misra, Daniel K. Molzahn
Accurate modeling of power flow behavior is essential for a wide range of power system applications, yet the nonlinear and nonconvex structure of the underlying equations often lim…
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…
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…
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…
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…