From the 1 of 12 linked papers with an AI index.
12 papers
Conditions for Quantum Advantage in AC Power Flow
Parikshit Pareek, Abhijith Jayakumar, Carleton Coffrin +1
This paper aims to contextualize the requirements for Quantum Computing (QC) algorithms to achieve a quantum advantage in solving the alternating current power flow (ACPF) problem,…
Gradient-Free Topology Adaptation for Power Flow Surrogates via In-Context Whitening
Ayushi Jolotia, Parikshit Pareek
The paper introduces In-Context Whitening, a gradient‑free method that adapts machine‑learned AC power‑flow surrogates to new network topologies by re‑estimating output whitening s…
Towards AC Feasibility of DCOPF Dispatch
Michael A. Boateng, Russell Bent, Sidhant Misra +3
DC Optimal Power Flow (DCOPF) is widely utilized in power system operations due to its simplicity and computational efficiency. However, its lossless, reactive power-agnostic model…
PACR: Parameter-Optimized AC Power Flow Restoration for AC Feasible DCOPF Dispatch
Michael A. Boateng, Russell Bent, Sidhant Misra +3
The DC optimal power flow is widely used in power system operations because of its computational efficiency and scalability. However, DC dispatches are not guaranteed to satisfy th…
Rethinking Neural Width for Alternating Current Optimal Power Flow Proxies
Dhruvi Khandelwal, Anurag Basistha, Ayushi Jolotia +1
Deep learning proxies for Alternating Current Optimal Power Flow (ACOPF) lack systematic methods for determining architectural size. This paper conducts a constructive thought expe…
Learning Power Flow with Confidence: A Probabilistic Guarantee Framework for Voltage Risk
Parikshit Pareek, Sidhant Misra, Deepjyoti Deka
The absence of formal performance guarantees in machine learning (ML) has limited its adoption for safety-critical power system applications, where confidence and interpretability…