- Outage Prediction and Grid Vulnerability Identification Using ...🔍
- Vulnerability Assessment of Power Grid Using Graph Topological ...🔍
- The Vulnerability of the Power Grid Structure🔍
- Electric Grid Outage Trends Make Case for Fuel Diversity🔍
- Advanced Grid Modeling🔍
- Systems and methods for outage prediction🔍
- Cyber Threat and Vulnerability Analysis of the U.S. Electric Sector🔍
- Power Grid Cascading Failure Prediction Based on Transformer🔍
Outage Prediction and Grid Vulnerability Identification Using ...
Outage Prediction and Grid Vulnerability Identification Using ...
This project will use big data and machine learning to develop data-driven prediction model for weather-induced customer power outages.
Vulnerability Assessment of Power Grid Using Graph Topological ...
This paper presents an assessment of the vulnerability of the power grid to blackout using graph topological indexes. ... The investigation finds that the ...
The Vulnerability of the Power Grid Structure: A System Analysis ...
Vulnerability analysis mainly is studied by using below main methodologies [20]. First, define the structural, logical and functional relations among all units ...
33 Argonne National Laboratory (2020), “Outage Prediction and Grid Vulnerability Identification Using Machine. Learning on Utility Outage ...
Advanced Grid Modeling | Argonne National Laboratory
A Novel Security Analysis Toolbox for National Grid Resilience Modeling · Outage Prediction and Grid Vulnerability Identification Using Machine Learning on ...
Systems and methods for outage prediction - Google Patents
A system and method for outage prediction for electrical distribution utilities using high- resolution weather forecasts, geographic data (e.g., land use ...
Cyber Threat and Vulnerability Analysis of the U.S. Electric Sector
potentially result in large scale power outages. Utilities are routinely faced with new challenges for dealing with these cyber threats to the grid and ...
Power Grid Cascading Failure Prediction Based on Transformer
Abstract. Smart grids can be vulnerable to attacks and accidents, and any initial failures in smart grids can grow to a large blackout because of.
Modeling electric grid vulnerability induced by natural events using ...
The same set of input datasets with a total of 47 features for each of the 17 counties in the Rio Grande, along with their historical power outage data, is used ...
Machine Learning Based Power Grid Outage Prediction in ...
A machine learning based prediction method is proposed in this paper to determine the potential outage of power grid components in response to an imminent ...
Machine learning for power outage prediction during hurricanes
A few of the grid hardening techniques are shown in Fig. 8. While ... identify patterns and predict future outages with a high degree of accuracy.
We hypothesize that specific anomaly detection applications can affect the training quality. Line outages differ from bus faults in at least two aspects: (i) ...
Increasing the resilience of the Texas power grid against extreme ...
We show that hardening only 1% of total lines can reduce the likelihood of the most destructive type of outage by a factor of between 5 and 20.
A Machine Learning Approach for Line Outage Identification in ...
Assessing the power grid vulnerability to extreme weather events based on long-term atmospheric reanalysis · Environmental Science, Engineering. Stochastic ...
A Comprehensive Survey on the Security of Smart Grid - arXiv
A specific instance of reconnaissance, known as Modbus Network Scanning, scans the network to identify devices operating with the Modbus ...
Predicting Storm Outages Through New Representations of Weather ...
Historical, geolocated power out- ages recorded by the Eversource Outage Management Sys- tem (OMS) were aggregated on the 2 km grid by storm. We identified the ...
Power outage prediction for natural hazards using synthetic power ...
Power outage prediction for natural hazards usually relies on one of two approaches, statistical models or fragility-based methods. Statistical models have ...
Grid Deployment Office Announces $4.6 Million Investment to ...
The University of Connecticut will use an outage prediction model, along with a risk assessment that takes into account the intersection of ...
Assessing grid hardening strategies to improve power system
"Assessing grid hardening strategies to improve power system performance during storms using a hybrid mechanistic-machine learning outage prediction model," ...
Deep-Belief Network Based Prediction Model for Power Outage in ...
This paper implements a proactive prediction model based on deep-belief networks that can predict imminent blackout. The proposed model is evaluated on a real ...