Contribution to a conference proceedings/Contribution to a book

FZJ-2023-03013

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Regulatory Changes in German and Austrian Power Systems Explored with Explainable Artificial Intelligence

Pütz, S. (Corresponding author) ; Kruse, J.FZJ* ; Witthaut, D.FZJ* ; Hagenmeyer, V. ; Schäfer, B.

2023
ACM New York, NY, USA

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Please use a persistent id in citations: doi:10.1145/3599733.3600247  doi:10.34734/FZJ-2023-03013

Abstract: A stable supply of electrical energy is essential for the functioning of our society. Therefore, energy and balancing markets of power grids are strictly regulated. With changes in technology, the economy and society, these regulations are also constantly adapted. However, whether these regulatory changes lead to the intended results is not easy to assess. Could eXplainable Artificial Intelligence (XAI) models distinguish regulatory settings and support the understanding of the effects of these changes? In this article, we explore two examples of regulatory changes: The splitting of the German-Austrian bidding zone and changes in the pricing schemes of the German balancing energy market. We find that boosted tree models and feedforward neural networks before and after a regulatory change differ in their respective parametrizations. Using Shapley additive explanations, we reveal model differences, e.g., in terms of feature importance, and identify key features of these distinct models. With this study, we demonstrate how XAI can be applied to investigate system changes in power systems.

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Contributing Institute(s):

1. Modellierung von Energiesystemen (IEK-10)

Research Program(s):

1. 1122 - Design, Operation and Digitalization of the Future Energy Grids (POF4-112) (POF4-112)
2. HDS LEE - Helmholtz School for Data Science in Life, Earth and Energy (HDS LEE) (HDS-LEE-20190612) (HDS-LEE-20190612)

Appears in the scientific report 2023

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