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Found 17 papers, 1 papers with code
Design and Validation of a Very Low-Power Phasor Measurement Unit
Phasor measurement units (PMUs) provide a high-resolution view of the power system at the locations where they are placed.
Analyzing Cross-Phase Effects of Reactive Power Intervention on Distribution Voltage Control
Increasing photovoltaic (PV) penetration in the distribution system can often lead to voltage violations.
High-Speed Voltage Control in Active Distribution Systems with Smart Inverter Coordination and Deep Reinforcement Learning
The increasing penetration of renewable energy resources in distribution systems necessitates high-speed monitoring and control of voltage for ensuring reliable system operation.
Creating Temporally Correlated High-Resolution Power Injection Profiles Using Physics-Aware GAN
Traditional smart meter measurements lack the granularity needed for real-time decision-making.
Analytical Verification of Performance of Deep Neural Network Based Time-Synchronized Distribution System State Estimation
Recently, we demonstrated success of a time-synchronized state estimator using deep neural networks (DNNs) for real-time unobservable distribution systems.
Cut-set and Stability Constrained Optimal Power Flow for Resilient Operation During Wildfires
Resilient operation of the power system during ongoing wildfires is challenging because of the uncertain ways in which the fires impact the electric power infrastructure (multiple arc-faults, complete melt-down).
Improving Photovoltaic Hosting Capacity of Distribution Networks with Coordinated Inverter Control -- A Case Study of the EPRI J1 Feeder
Adding photovoltaic (PV) systems in distribution networks, while desirable for reducing the carbon footprint, can lead to voltage violations under high solar-low load conditions.
Time-Synchronized State Estimation Using Graph Neural Networks in Presence of Topology Changes
Recently, there has been a major emphasis on developing data-driven approaches involving machine learning (ML) for high-speed static state estimation (SE) in power systems.
Data-Driven Flow and Injection Estimation in PMU-Unobservable Transmission Systems
Fast and accurate knowledge of power flows and power injections is needed for a variety of applications in the electric grid.
Time-Synchronized Full System State Estimation Considering Practical Implementation Challenges
We propose a Deep Neural network-based State Estimator (DeNSE) to overcome this problem.
Transmission Line Parameter Estimation Under Non-Gaussian Measurement Noise
The use of phasor measurement unit (PMU) data for transmission line parameter estimation (TLPE) is well-documented.
Representative Scenarios to Capture Renewable Generation Stochasticity and Cross-Correlations
When applied to historical data from a power utility, the proposed approach resulted in scenarios that included a good mix of seasonal and atypical days.
Mitigation of Saturated Cut-sets During Multiple Outages to Enhance Power System Security
The results obtained by analyzing different case-studies on the IEEE 118-bus and 2000-bus synthetic Texas systems indicate that the proposed two-component methodology successfully enhances the scope and speed of power system security assessment during multiple outages.
State and Topology Estimation for Unobservable Distribution Systems using Deep Neural Networks
Time-synchronized state estimation for reconfigurable distribution networks is challenging because of limited real-time observability.
Time Synchronized State Estimation for Incompletely Observed Distribution Systems Using Deep Learning Considering Realistic Measurement Noise
Time-synchronized state estimation is a challenge for distribution systems because of limited real-time observability.
Fast DTW and Fuzzy Clustering for Scenario Generation in Power System Planning Problems
Power system planning problems become computationally intractable if one accounts for all uncertain operating scenarios.
A Fixed-Flexible BESS Allocation Scheme for Transmission Networks Considering Uncertainties
Battery energy storage systems (BESSs) can play a key role in mitigating the intermittency and uncertainty associated with adding large amounts of renewable energy to the bulk power system (BPS).
