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Confidence-level optimization in distribution grids for voltage droop controllers tuning

This paper deals with a centralized tuning of the local controllers parameters in a distribution grid with many Distributed Generators. The optimal controllers settings are obtained by minimizing the confidence level of voltage spec- ification violations. The confidence level optimization problem uses Gaussian uncertainties of short-term forecasting and OLTC errors along with an accurate linear power flow approximation. Considering these assumptions, the optimization problem is shown to be convex and the characteristics of uncertainties are reduced to their means and standard deviations. The proposed method optimizes the full network while keeping the droop-like industrial structure of the controllers and allows to consider feeders which can have low and high voltages. The merits of the method are illustrated via a modified real distribution network showing a decrease of voltage variances and violations.

Author(s):

Jérôme Buire    
Ecole Centrale de Lille
France

Frédéric Colas    
Arts et Métiers ParisTech
France

Jean-Yves Dieulot    
Polytech Lille
France

Léticia De-Alvaro    
Enedis
France

Xavier Guillaud    
Ecole Centrale de Lille
France

 

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