On the Quantitatively Characterization of Intermittent Power Sources Uncertainty

TL;DR

This paper develops statistical functions to quantify the forecast uncertainty of intermittent power sources like wind and solar, using real historical data to improve power system reliability analysis.

Contribution

It introduces new statistical functions to characterize uncertainty in single and multiple intermittent power sources, validated with real-world data.

Findings

Negative-exponential uncertainty function for single sources

Statistical functions for multiple sources and total power

Effective quantification demonstrated with real data

Abstract

This paper designs a statistical quantification towards the intermittent power uncertainty in power systems. A negative-exponential forecast uncertainty function is constructed to represent the relationship between the statistics of forecast error of a single intermittent power source and time advance. Subsequently, other kinds of statistical functions are proposed to characterize the statistical uncertainty of multiple intermittent power sources and all power sources, namely the sum statistical functions, the equivalent statistical functions, and the contour statistical functions. Based on a large amount of historical observations, these functions are employed to statistically quantify the forecast uncertainty of a single intermittent power source, multiple intermittent power sources as well as all power sources. Historical data sampled from real wind farms and solar sites demonstrates the effectiveness of the proposed method.