Power and Energy
This dataset includes corona discharge images under AC, + DC, and - DC voltages. To generate corona discharge, three types of electrodes were used. These are the conical rod - plane, the hemispherical rod - plane, and the hemispherical rod - hemispherical rod. One electrode was connected to the high voltage, and the other was connected to the ground potential. A digital single-lens reflex (DLSR) camera was used to capture corona discharge images from corona inception to the gap breakdown.
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This paper presents the theory and key experimental findings for an investigation into the generation of bimodal resonance
(frequency splitting) phenomena in mutually over-coupled inductive sensors, and its exploitation to evaluate relative separation and
angular displacement between coils. This innovative measurement technique explores the bimodal resonant phenomena observed
between two coil designs - solenoid and planar coil geometries. The proposed sensors are evaluated against first-order analytical
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Database of the times the device remained in each state (idle, low power mode, transmitting and listening, respectively), number of hops, hop distance (d), transmission rate (_R) and size of the packet sent (_Nb), measured on the Tmote Sky device using an Aloha Puro protocol with RDC implemented in the Contiki operating system.
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DataSet used in learning process of the traditional technique's operation, considering different devices and scenarios, perform the commutation through Pure ALOHA protocol, and make the device to operate with the best possible configuration.The control of energy consumption is essential for the operation of battery-operated systems, such as those used in IoT networks and sensors. The algorithms commonly employed for this purpose involve optimization functions with considerable complexity and rigorous control of the test environment.
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The dataset encompasses a diverse array of electrical signals representing Power Quality Disturbances (PQD), both in single and combined forms, meticulously generated in adherence to the IEEE 1159 guideline. Crucially, the dataset includes both raw data and corresponding labels, facilitating supervised learning tasks and enabling the development and evaluation of classification algorithms.
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The Excel file contains samples of a laboratory-generated noisy voltage signal with a dc component under nonideal sampling.
This test signal is generated in a laboratory for assessing power frequency estimation algorithms.
The first column represents the sample time.
The second column represents the voltage signal samples.
The reference fundamental frequency is 46 Hz.
The nominal voltage amplitude is 10 V.
The actual sampling rate varies in the range of 9.99834~10.01027 kHz.
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The synthetic dataset was developed in the Power Electronics and Electrical Drive Laboratory (Laboratório de Eletrônica de Potência e Acionamento Elétrico – LEPAC, in portuguese) at the Federal University of Espírito Santo (UFES), Brazil. The dataset was generated from a computer simulation of a three-phase squirrel cage induction motor model with the insertion of faults in the rotor, specifically broken bars. The induction motor mathematical model with broken bar fault is based on reference [1].
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An experimental study was conducted on a high-voltage glass-type disc (LD-160) to investigate the effect of string arrangements on pollution and icing flashover characteristics. Two Artificial Neural Network (ANN) applications were developed to simulate and calculate the flashover voltage based on the experimental results. The test results showed that the inverted T-type arrangement can improve the pollution flashover voltage and increase the icing flashover voltage of insulator strings compared to the traditional arrangement of the I-string.
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The dataset contains integrating renewable energy sources into power grids, emphasizing the need for advanced data-driven optimization models for optimal power flow problems. The dataset, which includes comprehensive details on both load and generator buses, covering active and reactive power measurements and voltage magnitudes and angles for the modified IEEE 39 bus system with wind power integration, is ideally suited for data-driven power system analysis studies. The dataset was generated for a part of the experiments.
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