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Found 20 papers, 11 papers with code
Managing power balance and reserve feasibility in the AC unit commitment problem
Incorporating the AC power flow equations into unit commitment models has the potential to avoid costly corrective actions required by less accurate power flow approximations.
Security Constrained Optimal Power Shutoff
To address this gap, we propose the Security-Constrained Optimal Power Shutoff (SC-OPS) problem which uses post-contingency security constraints to model the impact of unexpected line faults when planning a PSPS.
PowerModelsADA: A Framework for Solving Optimal Power Flow using Distributed Algorithms
This paper presents PowerModelsADA, an open-source framework for solving Optimal Power Flow (OPF) problems using Alternating Distributed Algorithms (ADA).
Recursive Restoration Refinement: A Fast Heuristic for Near-Optimal Restoration Prioritization in Power Systems
The prioritization of restoration actions after large power system outages plays a key role in how quickly power can be restored.
High-quality Thermal Gibbs Sampling with Quantum Annealing Hardware
This work builds on those insights and identifies a class of small hardware-native Ising models that are robust to noise effects and proposes a procedure for executing these models on QA hardware to maximize Gibbs sampling performance.
Combinatorial Optimization
Vocal Bursts Intensity Prediction
Single-Qubit Fidelity Assessment of Quantum Annealing Hardware
Overall, the proposed QASA protocol provides a useful tool for assessing the performance of current and emerging quantum annealing devices.
Programmable Quantum Annealers as Noisy Gibbs Samplers
Drawing independent samples from high-dimensional probability distributions represents the major computational bottleneck for modern algorithms, including powerful machine learning frameworks such as deep learning.
A Flexible Storage Model for Power Network Optimization
This paper proposes a simple and flexible storage model for use in a variety of multi-period optimal power flow problems.
PowerModelsRestoration.jl: An Open-Source Framework for Exploring Power Network Restoration Algorithms
With the escalating frequency of extreme grid disturbances, such as natural disasters, comes an increasing need for efficient recovery plans.
PowerModelsDistribution.jl: An Open-Source Framework for Exploring Distribution Power Flow Formulations
In this work we introduce PowerModelsDistribution, a free, open-source toolkit for distribution power network optimization, whose primary focus is establishing a baseline implementation of steady-state multi-conductor unbalanced distribution network optimization problems, which includes implementations of Power Flow and Optimal Power Flow problem types.
Computational Engineering, Finance, and Science Systems and Control Signal Processing Systems and Control
The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms
Consequently, benchmarking studies using the seminal AC Optimal Power Flow (AC-OPF) problem have emerged as the primary method for evaluating these emerging methods.
Optimization and Control
The ISTI Rapid Response on Exploring Cloud Computing 2018
This report describes eighteen projects that explored how commercial cloud computing services can be utilized for scientific computation at national laboratories.
Juniper: An Open-Source Nonlinear Branch-and-Bound Solver in Julia
Nonconvex mixed-integer nonlinear programs (MINLPs) represent a challenging class of optimization problems that often arise in engineering and scientific applications.
Optimization and Control
Quantum Algorithm Implementations for Beginners
As quantum computers become available to the general public, the need has arisen to train a cohort of quantum programmers, many of whom have been developing classical computer programs for most of their careers.
Emerging Technologies Quantum Physics
PowerModels.jl: An Open-Source Framework for Exploring Power Flow Formulations
This work provides a brief introduction to the design of PowerModels, validates its implementation, and demonstrates its effectiveness with a proof-of-concept study analyzing five different formulations of the Optimal Power Flow problem.
Optimization and Control Computational Engineering, Finance, and Science
Evaluating Ising Processing Units with Integer Programming
The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, present new opportunities for hybrid-optimization algorithms that are hardware accelerated by these devices.
Probabilistic $N$-$k$ Failure-Identification for Power Systems
A general cutting-plane algorithm is proposed to solve the convex relaxation and linear approximations of the $N$-$k$ problem.
Systems and Control
The QC Relaxation: Theoretical and Computational Results on Optimal Power Flow
Convex relaxations of the power flow equations and, in particular, the Semi-Definite Programming (SDP) and Second-Order Cone (SOC) relaxations, have attracted significant interest in recent years.
Computational Engineering, Finance, and Science Optimization and Control
NESTA, The NICTA Energy System Test Case Archive
In recent years the power systems research community has seen an explosion of work applying operations research techniques to challenging power network optimization problems.
A Linear-Programming Approximation of AC Power Flows
Linear active-power-only DC power flow approximations are pervasive in the planning and control of power systems.
