Power and Energy
Peter O. Lauritzen and Cliff L. Ma proposed an approach for creating a physical model of reverse recovery for soft recovery diodes in 1991. The current paper demonstrates how to create the proper SPICE sub-circuit using only the specifications from the diode datasheet from the manufacturer. Software for characterization tools has been developed, tested, and is now openly accessible for use
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This work presents a sub-model of round or tubular wire with skin effect simulation. The model is based on numerical solving Maxwell's equations, using a time-domain simulator as a numerical analysis tool. The geometry of round wire is divided by the number of concentric tubes of variable thickness. Finite difference numerical equations for field and current density are adapted for the time-domain simulator. Voltage drop across the wire is calculated using current density in the outermost layer surface and external inductance of the wire.
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The paper describes the way of extending a basicdiode SPICE model for a possibility to simulate realistic reverserecovery of power diodes. The proposed macro model uses allbasic diode model characteristics and processes the diffusioncapacitance current for adjusting reverse recovery. A Windowsapplication tool was made to simplify creating a new diode SPICEsub-model using the manufacturer data sheet or measured data.Experimental data are presented for comparison of the proposedmodel and real diode reverse recovery
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This dataset provides a simulation file for the Interleaved Vienna Rectifier with Pulse-Frequency Modulation (IVR-PFM) topology, developed for three-phase, three-wire applications. The simulation is designed for use with PSIM software and is configured to operate with a 220 V, 60 Hz line input voltage, delivering 3 kW of output power at 800 V. The IVR-PFM behaves as a resistive load at the input, with the equivalent resistance defined as Re = 4Lmfs, where Lm is the magnetizing inductance and fs is the switching frequency.
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This dataset includes the original IAWE, REDD, and UKDALE datasets, as well as the pre-processed tensor data used in the research paper. The files with the .h5 extension are the original datasets, while the .npy files are the tensorized data used in the paper.
The IAWE dataset is a high-resolution energy consumption dataset collected from a single household in India, recorded at a 1-second interval. It includes data on various appliances such as air conditioners, refrigerators, and lighting systems, making it particularly useful for studying load patterns in developing countries.
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This dataset is collected to investigate detection algorithms for DC series arc faults on resource constrained devices. The data is current signal collected from test-bench build to simulate arc fault under various conditions according to the standard UL1699B. Different condition includes the power mode regulated by the elctronic load in the system for the simulation of different system dynamics under topology series and parallel.
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The given data contains the results from laboratory trials related to the paper "Optimizing Congestion Management andEnhancing Resilience in Low-Voltage Grids Using OPF and MPC Control Algorithms Through Edge Computing and IEC 61850 Standards" currently in publication in IEEE Access.
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This dataset presents the capacity fade data for eight Lithium Titanate Oxide (LTO) battery cells over progressive charge-discharge cycles. The measurements, recorded at intervals of 250 cycles up to 3500 cycles, track the aging effects on battery capacity over time. The aging procedure includes a rest period of 10 minutes between charging and discharging cycles. Each charging and discharging process was conducted with a constant current of 1 ampere (A). The maximum charge voltage was set to 2.75 volts (V), while the minimum discharge voltage was set at 1.30 V.
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451 Views
A number of disruptive technologies are expected to impact on future power systems (PS). Electric vehicles (EV), photovoltaic systems (PV), wind turbines (WT), energy storage systems (ESS), vehicle to grid (V2G), and demand response (DR) are seen as those with the most significant potential impact on the PS. Whereas various aspects of the integration of these six technologies into PS are well researched, the technologies are often studied in isolation from each other or in small subsets (e.g. PV and ESS).
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A transformer temperature rise test was conducted using a temperature rise recorder (JIK-8/16 Temperature Recorder) under room temperature conditions. With a water flow rate of 10L/min, the input active power was 393.23kW, the input reactive power was 305.64kvar, and the input current was 744.6A. The power loss was 8.5kW, resulting in a power conversion efficiency of 97.8%.
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398 Views