Big data has potential to unlock novel groundbreaking opportunities in power grid that
enhances a multitude of technical, social, and economic gains. As power grid technologies …

Intrusion Detection has been heavily studied in both industry and academia, but
cybersecurity analysts still desire much more alert accuracy and overall threat analysis in …

Machine learning techniques are being widely used to develop an intrusion detection
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …

The application of big data in the energy sector is considered as one of the main elements of
Energy Internet. Crucial and promising challenges exist especially with the integration of …

There are both economic and environmental urges for transition from the current outdated
power grid to a sensor-embedded smart grid that monitors system stability, integrates …

Model-based analysis tools, built on assumptions and simplifications, are difficult to handle
smart grids with data characterized by volume, velocity, variety, and veracity (ie, 4Vs data) …

With the increased variability and uncertainty of net load induced from high penetrations of
renewable energy resources and more flexible interchange schedules, power systems are …

As a significant application of energy, smart grid is a complicated interconnected power grid
that involves sensors, deployment strategies, smart meters, and real-time data processing. It …

The role of cities in reducing global greenhouse gas emissions is rapidly evolving, as
evidenced by significant growth in transnational municipal networks and local climate …

This paper provides a survey of big data analytics applications and associated
implementation issues. The emphasis is placed on applications that are novel and have …