Assessment of Load and Wind Power Uncertainty Modeling on Power Flow Analysis for Distribution Systems

Harnessing renewable energy in modern power systems demands precise modeling of uncertainties to ensure efficient and reliable operation and planning. This study investigates the intricate effects of load and wind power uncertainty on power flow results for distribution systems by employing two distinct scenario-based methodologies. The first approach integrates temporal harmony between load and wind power data, clustering them simultaneously to create cohesive scenarios. Conversely, the second approach independently models load and wind power scenarios before combining them to capture variability. In order to obtain clusters, k-means clustering method is utilized in both methods where 10000 scenarios are generated using Normal and Weibull distributions for load and wind power, respectively. These methodologies are applied to a modified 33-bus radial distribution system, examining power flows, voltage profiles, and power losses under different number of scenarios.