Assessing the impact of weather-induced uncertainties in large-scale electricity systems

TL;DR

This paper introduces a novel spectral analysis-based method for generating realistic weather scenarios to improve the robustness of large-scale power system planning amidst weather-induced uncertainties.

Contribution

It presents a new approach to simulate weather scenarios by spectral decomposition, enabling comprehensive analysis of weather impacts on large-scale energy systems.

Findings

Quantifies fluctuations in wind and solar power feed-in due to weather variability.

Demonstrates improved robustness in energy system modeling with weather scenario generation.

Provides a basis for resilient grid planning considering weather uncertainties.

Abstract

The future energy system will largely depend on volatile renewable energy sources and temperature-dependent loads, which makes the weather a central influencing factor. This article presents a novel approach for simulating weather scenarios for robust large-scale power system analysis. By applying different signal analysis methods, historical weather data is decomposed into its spectral components, processed appropriately, and then used to generate random, self-consistent weather data. In this process, any weather parameters of different locations can be considered, while their respective dependencies are mapped. The added value is demonstrated by coupling with a state-of-the-art large-scale energy system model for Europe. It is shown that the integrated consideration of different weather influences allows a quantification of the range of fluctuation of various parameters - such as the feed-in of wind and solar power - and thus provides the basis for future resilient grid planning approaches.