相关论文: Disruptive Event Classification using PMU Data in …

Objective: Conventional urodynamics (UDS) provide critical diagnostic information, but requires invasive dual catheterization and manual labeling of clinically important events. Wireless, catheter-free bladder function tests are becoming…

Large-scale rare events data are commonly encountered in practice. To tackle the massive rare events data, we propose a novel distributed estimation method for logistic regression in a distributed system. For a distributed framework, we…

Given that disturbances to the stable and normal operation of power systems have grown phenomenally, particularly in terms of unauthorized access to confidential and critical data, injection of malicious software, and exploitation of…

This paper focuses on analytical studies of the primary user (PU) traffic classification problem. Observing that the gamma distribution can represent positively skewed data and exponential distribution (popular in communication networks…

This paper proposes a new method to monitor and mitigate fault induced delayed voltage recovery (FIDVR) phenomenon in distribution systems using {\mu}PMU measurements in conjunction with a Reduced Distribution System Model (RDSM). The…

Anomaly detection is an important task in power systems. To make better use of the phasor measurement unit (PMU) data collected from a low observability power system for anomaly detection, a data dimensionality increment algorithm is…

Today's evolving power system contains an increasing amount of power electronic interfaced energy sources and loads that require a paradigm shift in utility operations. Sub-synchronous oscillations at frequencies around 13-15 Hz, for…

In case of high impact low probability events, in order to restore the critical loads of the distribution network as much as possible, it is necessary to employ all available resources such as microgrids and distributed generations. This…

With the phenomenal growth in renewable energy generation, the conventional synchronous generator-based power plants are gradually getting replaced by renewable energy sources-based microgrids. Such transition gives rise to the challenges…

Today, microgrids in distribution networks are in dire need of improvement to cope with economic challenges, human losses, and equipment placement issues. Today, there is the issue of scattered resources in distribution systems, which has…

Modern society is critically dependent on the services provided by engineered infrastructure networks. When natural disasters (e.g. Hurricane Sandy) occur, the ability of these networks to provide service is often degraded because of…

Modern smart grids rely on dense measurement infrastructures, communication links, and intelligent field devices. Although this improves supervision and control, it also increases vulnerability to cyber-physical disruptions. Operators must…

Power domination is a graph theoretic model which captures how phasor measurement units (PMUs) can be used to monitor a power grid. Fragile power domination takes into account the fact that PMUs may break or otherwise fail. In this model,…

Many real-life dynamical systems change abruptly followed by almost stationary periods. In this paper, we consider streams of data with such abrupt behavior and investigate the problem of tracking their statistical properties in an online…

This article studies disruption tolerant networks (DTNs) where each node knows the probabilistic distribution of contacts with other nodes. It proposes a framework that allows one to formalize the behaviour of such a network. It generalizes…

The problem of attacks on new generation network infrastructures is becoming increasingly relevant, given the widening of the attack surface of these networks resulting from the greater number of devices that will access them in the future…

We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using model point estimates to represent individual data items, we…

This research proposes a machine learning-based attack detection model for power systems, specifically targeting smart grids. By utilizing data and logs collected from Phasor Measuring Devices (PMUs), the model aims to learn system…

This paper extends the idea of the Thevenin equivalent into unbalanced 3{\phi} circuits and proposes a 3{\phi} long-term voltage stability indicator (VSI), that can identify critical loads in a system. Furthermore, in order to identify…

The prompt and accurate detection of faults and abnormalities in electric transmission lines is a critical challenge in smart grid systems. Existing methods mostly rely on model-based approaches, which may not capture all the aspects of…