Currently, cybersecurity in digital substations is a topic of wide interest for companies and the academic community, which demands for its study the analysis of datasets (i.e., traffic collected during the operation of a substation).
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The pulse parameter-editable nanosecond pulse power supply (NPPS) based on all-solid-state Marx power topology is one of the critical excitation sources for studying the characteristics of atmospheric pressure low-temperature plasma (APLTP), its efficient applications, and the regulation of discharge characteristic. We have developed a 20kV/400W nanosecond pulse power supply with editable pulse edge parameters to validate the effectiveness of the diode-capacitor network (DCN) method.
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<p>This dataset consists in an ANAREDE equivalent grid for the Bongi Substation, located in in the Brazilian city of Recife. It contains the configurations for both the year of 2023 and the forecasts for the year 2027. The file for the year 2027 takes into account that the reconfiguration will occur in this substation as suggested by the Brazilian institutions responsible for the operation and planning of the electrical system. The demand of energy was based on the research done by the brazilian institution of Empresa de Pesquisa Energética.
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Electric Vehicles Charging Station with Photovoltaic Panels
This dataset contains the model and simulation output results in Matlab/Simulink of a three-phase grid-connected charging station with PV panels for electric vehicles realized in a work submitted to the 13th IEEE International Conference and Exposition on Electrical and Power Engineering EPEi 2024, Iasi, Romania, October 17-19, 2024 (https://www.epe.tuiasi.ro/).
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<p>The dataset provided contains the active power profiles, measured in MW, of photovoltaic (PV) and wind power plants, along with the active power consumed by loads in a 33-node distribution network. The profiles span four distinct weeks, specifically the second weeks of January, May, August, and October in 2022. These weeks were selected to represent the different seasons, thereby ensuring a comprehensive analysis across varying seasonal conditions.
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This dataset contains:
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This PSIM model presents the Shuffled Frog Leaping Algorithm applied in a boost converter for maximum power point tracking. The traditional Perturb and Observe and Incremental Conductance are also available for comparisons.
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This study is utilized for submodule open-circuit fault detection uncertainty analysis of modular multilevel converters. The dataset consists of 8 uncertainty factors and 15 system variables under four operation scenarios. The 1000 sets of uncertainty factor samples are generated randomly as initial configuration of the system. The 15 system variables are obtained by 1000 Monte Carlo simulations. We found that there are 153 residual samples exceeded the threshold of 0.8, which indicated a high false alarm rate.
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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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