1 code implementation • 30 Dec 2020 • Shimiao Li, Amritanshu Pandey, Bryan Hooi, Christos Faloutsos, Larry Pileggi
Given sensor readings over time from a power grid, how can we accurately detect when an anomaly occurs?
1 code implementation • 7 May 2022 • Shimiao Li, Amritanshu Pandey, Larry Pileggi
This work formalizes a new concept of physical interpretability which assesses how a ML model makes predictions in a physically meaningful way and introduces an evaluation methodology that identifies a set of attributes that a practical method should satisfy.
no code implementations • 17 Mar 2021 • Aayushya Agarwal, Amritanshu Pandey, Larry Pileggi
Fast and accurate optimization and simulation is widely becoming a necessity for large scale transmission resiliency and planning studies such as N-1 SCOPF, batch contingency solvers, and stochastic power flow.
no code implementations • 14 May 2021 • Amritanshu Pandey, Shimiao Li, Larry Pileggi
Instead, a more distributed yet coordinated approach for grid operation and control will emerge that models and analyzes the grid with a larger footprint and deeper hierarchy to unify control of disparate T&D grid resources under a common framework.
no code implementations • 9 Jul 2021 • Naeem Turner-Bandele, Amritanshu Pandey, Larry Pileggi
Quantifying the impact of inverter-based distributed generation (DG) sources on power-flow distribution system cases is arduous.
no code implementations • 29 Sep 2021 • Shimiao Li, Amritanshu Pandey, Larry Pileggi
An accurate and up-to-date topology is critical for situational awareness of a power grid; however, wrong switch statuses due to physical damage, communication error, or cyber-attack, can often result in topology errors.
no code implementations • NeurIPS 2021 • Priya L. Donti, Aayushya Agarwal, Neeraj Vijay Bedmutha, Larry Pileggi, J. Zico Kolter
In recent years, the ML community has seen surges of interest in both adversarially robust learning and implicit layers, but connections between these two areas have seldom been explored.
no code implementations • 19 Nov 2021 • Naeem Turner-Bandele, Amritanshu Pandey, Larry Pileggi
Electricity systems are experiencing increased effects of randomness and variability due to emerging stochastic assets.
no code implementations • 2 Dec 2021 • Marko Jereminov, Larry Pileggi
This paper extends the theoretical foundation of Equivalent Circuit Programming to enable the fusion of optimization theory and algorithms with the numerical methods that utilize the domain-specific knowledge of power flow models.
no code implementations • 16 Apr 2022 • Shimiao Li, Amritanshu Pandey, Larry Pileggi
This work presents the design of AC line outage distribution factor created from the circuit-theoretic power flow models.
no code implementations • 15 Nov 2022 • Aayushya Agarwal, Carmel Fiscko, Soummya Kar, Larry Pileggi, Bruno Sinopoli
To find the value of the critical point, we propose a time step search routine for Forward Euler discretization that controls the local truncation error, a method adapted from circuit simulation ideas.
no code implementations • 21 Apr 2023 • Shimiao Li, Jan Drgona, Shrirang Abhyankar, Larry Pileggi
Recent years have seen a rich literature of data-driven approaches designed for power grid applications.
no code implementations • 24 May 2023 • Aayushya Agarwal, Larry Pileggi
In this work, we introduce a new centralized distributed optimization algorithm (ECADO) inspired by an equivalent circuit model of the distributed problem.
no code implementations • 21 Oct 2023 • Carmel Fiscko, Aayushya Agarwal, Yihan Ruan, Soummya Kar, Larry Pileggi, Bruno Sinopoli
We present a stochastic first-order optimization method specialized for deep neural networks (DNNs), ECCO-DNN.