USPCASE(a)-118: Scenario Reduction by Clustering 365-Day Solar, Wind, Hydro, and Load Variations in Modified NREL 118 Bus Test System for Modern Power Systems Simulations

Published: 15 May 2026| Version 3 | DOI: 10.17632/y857pymnf7.3
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Description

High penetration of renewable energy sources introduces significant seasonal variability in power system operation, requiring scenario reduction to avoid excessive simulations for ensuring effective planning. The data includes seasonal variations in hydro, wind, solar generation, and load demand for a modified NREL 118 bus test system that was available in format of a commercial software called PLEXOS. In contrast, this dataset has been converted to format for simulation in the open-source MATPOWER software. The hourly data of full year was processed for scenario reduction by k-means clustering to obtain 18 representative scenarios while preserving seasonal characteristics.

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Electrical Engineering, Machine Learning, Computer Simulation, Renewable Energy, Stationary Power Systems, Smart Grid

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