Search Results for author:
Found 23 papers, 4 papers with code
Long Duration Battery Sizing, Siting, and Operation Under Wildfire Risk Using Progressive Hedging
Extending traditional progressive hedging techniques, we consider coupling in both placement variables across all scenarios and state-of-charge variables at temporal boundaries.
Sample-Based Conservative Bias Linear Power Flow Approximations
The power flow equations are central to many problems in power system planning, analysis, and control.
Optimized LinDistFlow for High-Fidelity Power Flow Modeling of Distribution Networks
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.
Analysis of Fairness-promoting Optimization Schemes of Photovoltaic Curtailments for Voltage Regulation in Power Distribution Networks
In this work, we combine these two schemes and provide extensive analyses and comparisons of these two fairness schemes.
Improving Fairness in Photovoltaic Curtailments via Daily Topology Reconfiguration for Voltage Control in Power Distribution Networks
However, such schemes result in increased overall curtailments.
Fairness-aware Photovoltaic Generation Limits for Voltage Regulation in Power Distribution Networks using Conservative Linear Approximations
These limits are computed a day ahead of real-time operations by solving an offline stochastic optimization problem using forecasted scenarios for PV generation and load demand.
AC Power Flow Informed Parameter Learning for DC Power Flow Network Equivalents
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.
Optimally Managing the Impacts of Convergence Tolerance for Distributed Optimal Power Flow
The future power grid may rely on distributed optimization to determine the set-points for huge numbers of distributed energy resources.
Detecting Shared Data Manipulation in Distributed Optimization Algorithms
We evaluate the detection conditions' performance on three data manipulation strategies we previously proposed: simple, feedback, and bilevel optimization attacks.
Optimizing Parameters of the DC Power Flow
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.
Co-Optimization of Damage Assessment and Restoration: A Resilience-Driven Dynamic Crew Allocation for Power Distribution Systems
This study introduces a mixed-integer linear programming (MILP) model, effectively co-optimizing patrolling, damage assessment, fault isolation, repair, and load re-energization processes.
GreenEVT: Greensboro Electric Vehicle Testbed
Since both the transportation network and the power grid already experience periods of significant stress, joint analyses of both infrastructures will most likely be necessary to ensure acceptable operation in the future.
AC Power Flow Feasibility Restoration via a State Estimation-Based Post-Processing Algorithm
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.
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).
Conditions for Estimation of Sensitivities of Voltage Magnitudes to Complex Power Injections
Therefore, this paper addresses the conditions for estimating sensitivities of voltage magnitudes with respect to complex (active and reactive) electric power injections based on sensor measurements.
A Data-Driven Sensor Placement Approach for Detecting Voltage Violations in Distribution Systems
In this paper, we consider a sensor placement problem which seeks to identify locations for installing sensors that can capture all possible violations of voltage magnitude limits.
Restoring AC Power Flow Feasibility from Relaxed and Approximated Optimal Power Flow Models
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.
Improving Distribution System Resilience by Undergrounding Lines and Deploying Mobile Generators
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.
Sharing the Load: Considering Fairness in De-energization Scheduling to Mitigate Wildfire Ignition Risk using Rolling Optimization
However, there may be many combinations of power lines whose de-energization will result in about the same reduction of system-wide wildfire risk, but the associated power outages affect different communities.
Optimizing Transmission Infrastructure Investments to Support Line De-energization for Mitigating Wildfire Ignition Risk
To reduce wildfire ignition risks, power system operators preemptively de-energize high-risk power lines during extreme wildfire conditions as part of "Public Safety Power Shutoff" (PSPS) events.
A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow
We train our RL policy using deep Q-learning, and show that this policy can result in significantly accelerated convergence (up to a 59% reduction in the number of iterations compared to existing, curvature-informed penalty parameter selection methods).
Assessing the Impacts of Nonideal Communications on Distributed Optimal Power Flow Algorithms
Power system operators are increasingly looking toward distributed optimization to address various challenges facing electric power systems.
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
