Impact of Dependence on State Identification Results in Distribution Grids Using Copula Theory

Konferenz: NEIS 2017 - Conference on Sustainable Energy Supply and Energy Storage Systems
21.09.2017 - 22.09.2017 in Hamburg, Deutschland

Tagungsband: NEIS 2017

Seiten: 7Sprache: EnglischTyp: PDF

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Schmidt, Maximilian; Schegner, Peter (Technische Universität Dresden, Institute of Electrical Power Systems and High Voltage Engineering, Dresden, Germany)

Distribution system state identification belongs to one of the most fundamental parts of modern smart grid operation strategies. The quality of identified system states is essential for subsequent algorithms. This paper deals with the impact of dependence on state identification results. Therefore, dependent data samples are generated using Copula theory with different dependence characteristics. The results of multiple Monte Carlo simulations reveal a strong influence of both degree of dependence and dependence structure on state identification errors.