The dataset contains an example of energy consumption, Functioning hours and Production KPI of different stages of the experimental open pit mine, mainly the destoning, the screening, and the train loading station. The Code is an example of the prediction algorithm, and the API can be used to apply the same algorithm used in this article.

In the proposed Dataset the energy consumption data for each station are collected from power meters and stored into a database that contains functioning hours and production.


In this report, system parameters and additional information are provided to complement the data of the paper: “Virtual Synchronous Generator for VSC-HVDC Stations with DC Voltage Control”.


The database contains information about three test systems, including the network connected to Bus 5 of the Roy Billinton Test System and two netwroks with 93 and 135 load nodes.




The dataset represents the input data on which the article Bayesian CNN-BiLSTM and Vine-GMCM Based Probabilistic Forecasting of Hour-Ahead Wind Farm Power Outputs, is based. The data consist of a two-year hourly time series of measured wind speed and direction, air density, and production of two wind farms (WTs) in Croatia (Bruška and Jelinak). In addition to the two listed WTs, measurements of two nearby WTs (Glunca and Zelengrad) are also attached in training files (these WPPs are not directly analyzed in the article).


The switching cell with switching frequency modulation (SC-SFM) has several benefits with respect to power conversion. Some of the most important features are those present in the boost variation, denominated as interleaved boost converter with switching frequency modulation (IBC-SFM). The converter conciliates some CCM characteristics, such as, continual conduction in the input inductor and limited current effort in the active components, with characteristics of some DCM converters, such as, resistive behavior for the input, soft-switching and no reverse recovery for the diodes.


This dataset includes the bus and branch informations of the IEEE RTS-79 system and Korean transmission network. The information of branch is decribed by impednace matrix. 

The dataset is for the paper titled: "Evaluation for Maximum Allowable Capacity of Renewable Energy Source Considering AC System Strength Measures".


The dielectric spectroscopy data was obtained to characterize the dielectric responses and calculate the dielectric loss in the FEM model. The complex dielectric permittivity was measured with the Novocontrol Concept 80 broadband dielectric spectrometer. Silver electrode with a diameter of 30 mm was prepared on both sides of the sample by sputtering. The temperature range in this experiment was from -30 to 150 °C with an interval of 10 °C. The frequency range was from 1 Hz to 1 MHz.



Most present wireless power transfer (WPT) systems are designed for 400-V EVs and its compatibility for a higher battery pack voltage is barely studied. To adapt for different WPT charging scenarios, this paper proposes a resonant inductor integrated-transformer (RIIT) based receiver. The design guideline, power losses, and power transfer capacity of the proposed system are presented. The proposed receiver is compact, low-cost, reliable, easy-to-implement, and compatible for WPT systems with different battery pack voltages without any significant change of system parameters.


This dataset contains the hourly system marginal price (SMP) of South Korea and daily fuel prices (WTI, Henry Hub, Brent, NBP) data from 2002 to 2020, and the oil price scenarios from 2019 to 2050 are also attached.

The dataset is for the letter entitled: "Fuel Price Based Long-Term Hourly System Marginal Price Scenario Generation".