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UVQCaseData

The power generation and load data in the case studies of the paper "Modeling, Prediction, and Risk Management of Distribution System Voltages with Non-Gaussian Probability Distributions".
The active power outputs of photovoltaic units are obtained using the actual solar irradiation data provided by SolarAnywhere [1]. The load data are obtained by normalizing the load drawn from real-world measurements [2], and then multiplying it by the average load from the original load data of the systems [3], [4].

Power Generation and Load Configuration

The modified IEEE 33-bus system contains 4 PV units and 32 loads. The nominal power generation of each PV unit is 1 MW and the average load of each bus is found in [3].
The modified IEEE 123-bus system contains 9 PV units and 85 loads. The nominal power generation of each PV unit is 0.8 MW and the average load of each bus is found in [4].

File Format

".mat" type of Matlab.
"IEEE33_PV&Load_Data.mat' is the data file in the modified IEEE 33-bus system.
"IEEE123_PV&Load_Data.mat' is the data file in the modified IEEE 123-bus system.

Variable Format

"PV_hourly_normalized" is the hourly data of the normalized active power of PV units, of which each column represents a PV unit. The base value for the normalization of each PV unit is the nominal power generation of each PV unit.
"load_hourly_normalized" is the hourly data of the normalized loads, of which each column represents a load. The base value for the normalization of each load is the average value of each load.
"timeLabel_hourly" is the time label of the hourly data from Jan. 1, 2011 to Dec. 31, 2014.

References

[1] [Online]. Available: https://data.solaranywhere.com/Data/Public
[2] Trindade, Artur. ElectricityLoadDiagrams20112014. UCI Machine Learning Repository, 2015. doi: 10.24432/C58C86.
[3] S. K. Goswami and S. K. Basu, “A new algorithm for the reconfiguration of distribution feeders for loss minimization,” IEEE Trans. Power Del., vol. 7, no. 3, pp. 1484–1491, Jul. 1992, doi: 10.1109/61.141868.
[4] L. Bobo, A. Venzke, and S. Chatzivasileiadis, “Second-order cone relaxations of the optimal power flow for active distribution grids: Comparison of methods,” Int. J. Electr. Power Energy Syst., vol. 127, 106625, May 2021, doi: 10.1016/j.ijepes.2020.106625.

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The power generation and load data in the case studies of the paper "Uncertain Voltage Quantification for Risk-Constrained Volt/Var Optimization in Power Distribution Systems"

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