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- Data for: A two-stage stochastic programming approach for non-cooperative generation maintenance scheduling model designwe examined the proposed model with ieee reliability test (32 bus)
- Dataset
- Data for: Universal Branch Model for the Solution of Optimal Power Flows in Hybrid AC/DC GridsTest cases for the Paper Universal Branch Model for the Solution of Optimal Power Flows in Hybrid AC/DC Grids
- Dataset
- Data for: Unit Scheduling Considering the Flexibility of Intelligent Temperature Control Appliances under TOU Power PriceThe dataset contains wind power, electricity price and some system parameters.
- Dataset
- Data for: Research on optimal allocation strategy of multiple energy storage in regional integrated energy system based on increment of operation benefitThe datas in this file are the datas of electric load, cooling load and heating load required by users in the industrial park in this example, as well as the predicted output data of fan and photovoltaic.
- Dataset
- Data for: Wavelet Group Method of Data Handling for Fault Prediction in Electrical Power InsulatorsOriginal signal from ultrasound equipment.
- Dataset
- Data for: Online Synchronous Generator Out-of-Step Prediction by Ellipse Fitting on Acceleration Power - Speed Deviation CurveThe Digsilent simulation file is uploaded: IEEE 39 bus system
- Dataset
- Data for: Fault prediction of gas-insulated system with hypersensitive optical monitoring and spectral informationData for Fig. 1. Phase-resolved scatterplots (φ, q), double-spectral scatterplots (Iband1, Iband2) for corona discharges occurring along the needle-plane gaps with different gap distances (d). (a)-(c): (φ, q); (d)-(f): (Iband1, Iband2); Data for Fig. 2. Integral spectra of the corona discharge in SF6 (gap distance = 50 mm; gas pressure = 0.3 MPa; f = 15). A fiber-optic spectrometer (200-1150 nm), a collecting lens installed outside the quartz glass window of the test chamber, and a 19-core silica fiber were employed to measure the integral spectra of the discharges. Data for Fig. 7. Light intensity stochastic distributions in a RGB 3-D coordinate system for the three types of defect. Data for Fig. 11. Scatterplots of the DBSCAN clustering results for a double-sourced discharge (floating discharge and creeping discharge occur simultaneously with a discharge level of 320 pC). Data for Fig. 15. Results of clustering analysis on TSS data (Cluster 1 and Cluster 2) and the evolution paths of the two types of discharge (Corona discharge: 30 μJ→93 μJ; Floating discharge: 77 μJ→224 μJ).
- Dataset
- Data for: Improved electromagnetic coil insulation health monitoring using equivalent circuit model analysisTotal number of measurements: 64 For data file “Valve4_DCR_data.mat”: The third column of DCR_avg is the average DC resistance at each time. T is the measurement times. For the data file “Valve4_RX_data.mat”: f is the frequency vector rH is the resistance (real part of impedance) data for the healthy coil (i.e., before the formation of a short) rHCorr is the correlation of rH with time (Spearman correlation spectrum) xH is the reactance (imaginary part of impedance) data for the healthy coil (i.e., before the formation of a short) R_avg is the resistance (real part of impedance) data for the entire experiment X_avg is the reactance (imaginary part of impedance) data for the entire experiment R_corr is the Spearman correlation of the resistance with time for the entire experiment X_corr is the Spearman correlation of the reactance with time for the entire experiment T is the measurement time vector res is the index for the resonant frequency over the entire experiment (i.e., f(res) is the resonant frequency over the entire experiment) Zmag_avg is the impedance magnitude measurements over the entire experiment Zpha_avg is the impedance phase (in degrees) measurements over the entire experiment
- Dataset
- Data for: AutoSynGrid: A MATLAB-based Toolkit for Automatic Generation of Synthetic Power GridsGenerated synthetic power grids by AutoSyngrid toolkit with three reference systems of NYISO, WECC, and ERCOT
- Dataset
- Data for: Power system state estimation with extended power formulationsPower system state estimation with extended power formulations. Example on 2 systems with the IEEE European Low Voltage Time Series.
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