This .zip file contains two files: Temperature_outdoor.xlsx and TestData.xlsx. This .zip file provides detailed configuration information of the case system mentioned in artical "Dynamic Optimal Energy Flow in the Heat and Electricity Integrated Energy System".

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This paper utilizes modern statistical and machine learning methodology to track oscillation modes in complex power engineering systems. The damping ratio of the electromechanical oscillation mode is formulated as a function of power of the generators and loads as well as bus voltage magnitudes in the entire power system. The celebrated Lasso algorithm is implemented to solve this high-dimension modeling problem. By the nature of the $L_1$ design, the Lasso algorithm can automatically render a sparse solution, and by eliminating redundant features, it provides desirable prediction power.

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611 Views

Geomagnetic field variations produce geoelectric fields that can affect the operation of technological networks at the Earth’s surface, including power systems, pipelines, phone cables and railway circuits. To assess the geomagnetic hazard to this technology, it is necessary to model the geomagnetically induced currents (GIC) produced in these systems during geomagnetic disturbances. This requires use of geomagnetic data with appropriate Earth conductivity models to calculate the geoelectric fields that drive GIC.

Instructions: 

The dataset contains files of geomagnetic and geoelectric field values generated by analytic calculations. These are provided for testing software used for calculating geoelectric fields produced by geomagnetic disturbances.

The geomagnetic field dataset is to be used as a test input to geoelectric field calculation software.

The analytic geoelectric field datasets are to be used for checking the output from geoelectric field calculation software.  The paper (Boteler et al, 2019) shows the accuracy that can be achieved with real software if the calculations are set up correctly.

Two sets of data are provided:  One sampled once a second and containing 7 frequency components, and one sampled once a minute and containing 6 frequency components (ie with the highest frequency component removed).

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The files in this dataset each contain vectors Time, PEDAL, SPEED, ACCEL, VOLTAGE and CURRENT related to an Electric Vehicle travelling on one of four different roads, mostly in urban areas.  Data is obtained from the CAN bus of the vehicle (a Zhidou ZD model ZD2) resampled in order to obtain a single time coordinate and stored in the dataset.

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1675 Views

This folder contains two csv files and one .py file. One csv file contains NIST canopy PV plant data imported from https://pvdata.nist.gov/. This csv file has 1041 days raw data consisting PV plant POA irradiance, ambient temperature, Inverter DC current, DC voltage, AC current and AC voltage. Second csv file contains user created data. The Python file imports two csv files. The Python program executes four proposed corrupt data detection methods to detect corrupt data in NIST canopy PV plant data.

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989 Views

We investigated the turn-off waveforms of Superjunction (SJ) silicon MOSFETs with respect to their own charge imbalance by experiments as well as by device simulations.When SJ-MOSFETs are used for chopper circuits we find a unique hump in the current waveform during the turn-off transient. The magnitude of the hump shape waveform drastically depends on the charge imbalance (CIB) in the SJ structure.

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superjunction mosfets turn-off switching waveforms

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131 Views

This dataset is in support of my research paper  '     PFC '.  

Preprint :

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4507 Views

 This dataset is in support of my research paper 'Comparative Control Loop Stability & Eigen Analysis of Transfer Functions in 7.5 Hp BLDC Sensorless SMO'.

Preprint :

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6241 Views

Dynamic data for frequency control with continuous UFLS and LCFB1

This dataset is supplementary material to the draft 'Continuous Under-Frequency Load Shedding Scheme for Power System Adaptive Frequency Control' submitted to IEEE Transactions on Power Systems. Authors of the draft are: Changgang Li, Member, IEEE, Yue Wu, Yanli Sun, Hengxu Zhang, Member, IEEE, Yutian Liu, Senior Member, IEEE, Yilu Liu, Fellow, IEEE, and Vladimir Terzija, Fellow, IEEE

 

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