相关论文: Outage Detection in Partially Observable Distribut…
Machine learning (ML) has been extensively adopted for the online sensing-based monitoring in advanced manufacturing systems. However, the sensor data collected under abnormal states are usually insufficient, leading to significant data…
Phasor measurement units (PMUs) create ample real-time monitoring opportunities for modern power systems. Among them, line outage detection and identification remains a crucial but challenging task. Current works on outage identification…
The increasing penetration of distributed energy resources in low-voltage networks is turning end-users from consumers to prosumers. However, the incomplete smart meter rollout and paucity of smart meter data due to the regulatory…
The changes in the electric energy system toward a sustainable future are inevitable and already on the way today. This often entails a change of paradigm for the electric energy grid, for example, the switch from central to decentralized…
Online transmission line outage detection over the entire network enables timely corrective action to be taken, which prevents a local event from cascading into a large scale blackout. Line outage detection aims to detect an outage as soon…
Tampering of metering infrastructure of an electrical distribution system can significantly cause customers' billing discrepancy. The large-scale deployment of smart meters may potentially be tampered by malware by propagating their agents…
The identification of out-of-distribution content is critical to the successful implementation of neural networks. Watchdog techniques have been developed to support the detection of these inputs, but the performance can be limited by the…
In order to keep track of the operational state of power grid, the world's largest sensor systems, smart grid, was built by deploying hundreds of millions of smart meters. Such system makes it possible to discover and make quick response to…
Power system outages expose market participants to significant financial risk unless promptly detected and hedged. We develop an outage identification method from public market signals grounded in the parametric quickest change detection…
This work presents a topology detection method combining home smart meter information and sparse line flow measurements. The problem is formulated as a spanning tree detection problem over a graph given partial nodal and edge flow…
Due to the large volume of heterogeneous data provided by both the customer and the grid side, a big data visualization platform is built to discover the hidden useful knowledge for smart grid (SG) operation, control and situation…
Anomaly detection is concerned with a wide range of applications such as fault detection, system monitoring, and event detection. Identifying anomalies from metering data obtained from smart metering system is a critical task to enhance…
Despite society's strong dependence on electricity, power outages remain prevalent. Standard methods for directly measuring power availability are complex, often inaccurate, and are prone to attack. This paper explores an alternative…
We propose a novel unsupervised anomaly detection approach using generative adversarial networks and SOP-derived spectrograms. Demonstrating remarkable efficacy, our method achieves over 97% accuracy on SOP datasets from both submarine and…
We propose a novel method for imputing missing data by adapting the well-known Generative Adversarial Nets (GAN) framework. Accordingly, we call our method Generative Adversarial Imputation Nets (GAIN). The generator (G) observes some…
Since transmission lines are crucial links in the power system, one line outage event may bring about interruption or even cascading failure of the power system. If a quick and accurate line outage detection and localization can be…
Despite outstanding semantic scene segmentation in closed-worlds, deep neural networks segment novel instances poorly, which is required for autonomous agents acting in an open world. To improve out-of-distribution (OOD) detection for…
In this paper we present novel methodology for automatic anomaly and switch event filtering to improve load estimation in power grid systems. By leveraging unsupervised methods with supervised optimization, our approach prioritizes…
This paper considers the real-time power quality monitoring in power grid systems. The goal is to detect the occurrence of disturbances in the nominal sinusoidal voltage/current signal as quickly as possible such that protection measures…
To address the challenges and exploit the opportunities that the decarbonization of the energy sector is bringing about, advanced distribution network management and operation strategies are being developed. Many of these require accurate…