Learning from class-imbalanced data: Review of methods and applications
Rare events, especially those that could potentially negatively impact society, often require
humans' decision-making responses. Detecting rare events can be viewed as a prediction …
humans' decision-making responses. Detecting rare events can be viewed as a prediction …
Fault diagnostics in smart micro-grids: A survey
Due to rising awareness on environmental protection and for maintenance of clean
habitable communities, current and next generation micro-grids are desired to have …
habitable communities, current and next generation micro-grids are desired to have …
A survey on unbalanced classification: How can evolutionary computation help?
Unbalanced classification is an essential machine learning task, which has attracted
widespread attention from both the academic and industrial communities due mainly to its …
widespread attention from both the academic and industrial communities due mainly to its …
A multiagent design for power distribution systems automation
MJ Ghorbani, MA Choudhry… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
A new multiagent system (MAS) design for fault location, isolation, and restoration in power
distribution systems (PDSs) is presented. When there is a fault in the PDS, MAS quickly …
distribution systems (PDSs) is presented. When there is a fault in the PDS, MAS quickly …
Data-driven classifier for extreme outage prediction based on Bayes decision theory
The growing concern over catastrophic weather events, mostly as a direct result of climate
changes, has underscored the need for expanding traditional power system contingency …
changes, has underscored the need for expanding traditional power system contingency …
Predicting thunderstorm-induced power outages to support utility restoration
Strong thunderstorms have substantial impacts on power systems, posing risks and
inconveniences due to power outages. Developing models predicting the outages before a …
inconveniences due to power outages. Developing models predicting the outages before a …
Dual-channel convolutional network-based fault cause identification for active distribution system using realistic waveform measurements
Accurate and rapid identification of distribution system fault causes is essential for power
system reliability enhancement. Manual fault cause identification requires extensive human …
system reliability enhancement. Manual fault cause identification requires extensive human …
Optimal protection coordination in the micro-grid including inverter-based distributed generations and energy storage system with considering grid-connected and …
This paper presents the optimal protection coordination (OPC) to grid-connected and
islanded micro-grid (MG) consisting renewable energy sources (RESs), and energy storage …
islanded micro-grid (MG) consisting renewable energy sources (RESs), and energy storage …
Optimal placement of fault indicators using the immune algorithm
CY Ho, TE Lee, CH Lin - IEEE Transactions on Power Systems, 2010 - ieeexplore.ieee.org
This paper examines the application of the immune algorithm for the problem of optimal
placement of fault indicators to minimize the total cost of customer service outage and …
placement of fault indicators to minimize the total cost of customer service outage and …
Fault diagnosis, service restoration, and data loss mitigation through multi-agent system in a smart power distribution grid
Smart power distribution grid is equipped with different sensors and smart meters for getting
measurements at different nodes. Additionally, for monitoring and control purpose Intelligent …
measurements at different nodes. Additionally, for monitoring and control purpose Intelligent …