no code implementations • 8 Apr 2024 • Babak Taheri, Rahul K. Gupta, Daniel K. Molzahn
Using sensitivity information, our algorithm optimizes the LinDistFlow approximation's coefficient and bias parameters to minimize discrepancies in predictions of voltage magnitudes relative to the nonlinear DistFlow model.
no code implementations • 22 Nov 2023 • Babak Taheri, Daniel K. Molzahn
This paper presents an algorithm to optimize the parameters of power systems equivalents to enhance the accuracy of the DC power flow approximation in reduced networks.
no code implementations • 30 Sep 2023 • Babak Taheri, Daniel K. Molzahn
Inspired by techniques for training machine learning models, this paper proposes an algorithm that seeks optimal coefficient and bias parameters to improve the DC power flow approximation's accuracy.
no code implementations • 15 Sep 2023 • Ali Jalilian, Babak Taheri, Daniel K. Molzahn
This study introduces a mixed-integer linear programming (MILP) model, effectively co-optimizing patrolling, damage assessment, fault isolation, repair, and load re-energization processes.
no code implementations • 22 Apr 2023 • Babak Taheri, Daniel K. Molzahn
By automatically learning the trustworthiness of various outputs from simplified OPF problems, these parameters inform the online computations of the state estimation-based algorithm to both recover feasible solutions and characterize the performance of power flow approximations, relaxations, and ML models.
no code implementations • 9 Sep 2022 • Babak Taheri, Daniel K. Molzahn
Inspired by state estimation (SE) techniques, this paper proposes a new method for obtaining an AC power flow feasible point from the solution to a relaxed or approximated optimal power flow (OPF) problem.
no code implementations • 21 Apr 2022 • Babak Taheri, Daniel K. Molzahn, Santiago Grijalva
Using an extended version of the IEEE 123-bus test system, numerical simulations show that combining the ability to underground distribution lines with the deployment of mobile generators can significantly improve the resilience of the power supply to critical loads.
