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Anomaly detection in Phasor Measurement Unit (PMU) data requires high-quality, realistic labeled datasets for algorithm training and validation. Obtaining real field labelled data is challenging due to privacy, security concerns, and the rarity of certain anomalies, making a robust testbed indispensable. This paper presents the development and implementation of a Hardware-in-the-Loop (HIL) Synchrophasor Testbed designed for realistic data generation for testing and validating PMU anomaly detection algorithms.

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<p>The dataset forwas collected by UAVs equipped with camera heads to capture images of insulators on power transmission lines. These images have a resolution of 3872×2592 pixels. A total of 488 insulator defect images were selected, and the data was annotated using the LabelMe annotation software. This study's dataset annotated four types of labels: insulator, damaged, Flashover, and hammer. The insulator is a positive class label, and damaged, Flashover, and hammer are negative class labels.

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This letter proposes a virtual slack bus Newton-Raphson power flow (VSB-NRPF) algorithm serving for the PF analysis of droop-controlled medium-voltage direct current (MVDC) systems operating in islanded mode without a slack bus. In the proposed algorithm, one of the original power, current, power/voltage and current/voltage buses is assumed to be a virtual slack bus with an initial rated dc voltage, the value of which is corrected based on the actual PF balance equation at the original bus.

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The Illinois 200-Bus Cyber-Physical System (CPS) serves as an important case for studying risk analysis through the integration of physical and cyber components. This system designed to reflect real-world architectures. Access Complexity scores are assigned to its network edges based on the Common Vulnerability Scoring System (CVSS) Access Complexity (AC), allowing for the simulation of adversarial pathways within the system.

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Smart grids are nowadays featured by distributed energy resources, both renewables, traditional sources and storage systems. Generally, these components are characterized by different control technologies that interact with the generators through smart inverters. This exposes them to a variety of cyber threats. In this context, there is a need to develop datasets of attacks on these systems, in order to evaluate the risks and allow researchers to develop proper monitoring algorithms.

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Load data from three actual datasets. The first dataset is from Homestead on the southeast coast of Florida and covers electricity load data from January 1, 2018 to June 22, 2020 and corresponding weather forecast data. The second dataset includes energy consumption data from smart meters installed in London homes. We selected data from 5,567 London households spanning the period from November 24, 2011 to February 27, 2014 participating in the Low Carbon London project led by UK Power Networks.

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It proposes a lossless and stateless compression method for IEC 61850 Sampled Values flows. A set of bitmaps is introduced to indicate the size in bytes of the sampled currents and voltages, and to flag the presence or absence of the Quality field. The method has been evaluated for different profiles, and it can provide bandwidth savings between 30 and 52%, with a very low computational cost as a counterpart. It has been implemented and tested in two different hardware platforms, with traffic generated by a Merging Unit.

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The Kirk circle is a simple and effective method for representing power graphs and visualizing their topology. In general, nodes (buses) in an electrical network are numbered with neighboring nodes assigned consecutive or closely proximal numbers. This allows for sequential mapping of these nodes in increasing order of their numerical labels to evenly spread points on a Kirk circle. In the Kirk circle, the edge connections (branches) between nodes are indicated by straight lines (chords) between the appropriate points on the circle.

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ER-SPG is a Matlab code for producing synthetic power graphs using well-known Erdos-Renyi Random Model. It scales power graphs and achieves connectivity in each scale by different approach, and accordingly connected graphs with average degree between 2 to 5 (normally between 2.3 to 3.1) can be produced by ER_SPG with the structures similar to power graphs. It also reorders the graph vertices to obtain consecutive numbering similar to power graphs. This algorithm is also provides locations of zero injection buses (ZIBs) as operational data of power graphs.

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