An Analytical Probabilistic Expression for Modeling Sum of Spatial-dependent Wind Power Output

TL;DR

This paper introduces an analytical probabilistic model for the combined wind power output of spatially dependent wind farms, using advanced statistical tools to better capture uncertainty in smart grid applications.

Contribution

It develops a novel analytical expression incorporating copulas and Gaussian mixture models to accurately model spatial dependencies in wind farm outputs.

Findings

Model validated through Monte Carlo simulations.

Provides a more accurate representation of wind power uncertainty.

Enhances smart grid reliability and planning.

Abstract

Applying probability-related knowledge to accurately explore and exploit the inherent uncertainty of wind power output is one of the key issues that need to be solved urgently in the development of smart grid. This letter develops an analytical probabilistic expression for modeling sum of spatial-dependent wind farm power output through introducing unit impulse function, copulas, and Gaussian mixture model. A comparative Monte Carlo sampling study is given to illustrate the validity of the proposed model.