Impact of Current Market Developments in Europe on Deterministic Grid Frequency Deviations and Frequency Restauration Reserve Demand

Weibbach, Tobias; Remppis, Simon; Lens, Hendrik

doi:10.1109/eem.2018.8469210

Cited by 10 publications

(9 citation statements)

References 1 publication

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“…The low importance of ramps in the aFRR model suggests that DFDs are mostly compensated by primary control. The low importance of DFDs for the aFRR activation is consistent with other studies that show a strong decrease in deterministic aFRR peaks between 2012 and 2018 due to the introduction of 15min intra-day trading in December 2011 [4], [5].…”

Section: Ex-post Analysis Of Afrr Operationsupporting

confidence: 91%

“…The large impact of actual load and scheduled generation (with reverse signs) suggests that the difference between actual load and scheduled generation per 15min interval is very relevant for the aFRR. This intuitively makes sense as the aFRR activation depends on the area control error, see also [5].…”

Section: Ex-post Analysis Of Afrr Operationmentioning

confidence: 99%

“…Similarly, ref. [5] applies a data-driven analysis to examine the impact of 15 min intra-day trading on imbalances and control volumes in Germany. Apart from ex-post analysis, data-driven prediction methods have been developed for the aFRR market to allow for optimal bidding strategies [6].…”

Section: Introductionmentioning

confidence: 99%

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Secondary control activation analysed and predicted with explainable AI

Kruse,

Schäfer,

Witthaut

2021

Preprint

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The transition to a renewable energy system poses challenges for power grid operation and stability. Secondary control is key in restoring the power system to its reference following a disturbance. Underestimating the necessary control capacity may require emergency measures, such as load shedding. Hence, a solid understanding of the emerging risks and the driving factors of control is needed. In this contribution, we establish an explainable machine learning model for the activation of secondary control power in Germany. Training gradient boosted trees, we obtain an accurate description of control activation. Using SHapely Additive exPlanation (SHAP) values, we investigate the dependency between control activation and external features such as the generation mix, forecasting errors, and electricity market data. Thereby, our analysis reveals drivers that lead to high reserve requirements in the German power system. Our transparent approach, utilizing open data and making machine learning models interpretable, opens new scientific discovery avenues.

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Section: Ex-post Analysis Of Afrr Operationsupporting

confidence: 91%

Section: Ex-post Analysis Of Afrr Operationmentioning

confidence: 99%

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Secondary control activation analysed and predicted with explainable AI

Kruse,

Schäfer,

Witthaut

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…7 Such univariate analyses cannot be adjusted for effects of other features, which could be correlated with the feature of interest and may lead to incorrect conclusions (cf. Weißbach et al 42 ). Moreover, univariate, linear dependency analyses underestimate the effects of nonlinearities and ignore feature interactions.…”

Section: Discussionmentioning

confidence: 99%

“…8 A correlation between load and solar ramps as well as trading volumes reflects the role of solar power in power balancing. 42 The relation between wind power generation and large frequency increments in the CE grid has been studied using conditional probabilities by Haehne et al 7 Although existing studies provide us with essential insights into power system operation and frequency stability, they are limited in two ways. Firstly, linear correlation analyses cannot capture nonlinear dependencies and may thus underestimate or even overlook important effects.…”

Section: Frequency Stability: Indicators and Influencesmentioning

confidence: 99%