abstract: Synthetic power system test cases offer a wealth of new data for research and development purposes, as well as an avenue through which new kinds of analyses and questions can be examined. This work provides both a methodology for creating and validating synthetic test cases, as well as a few use-cases for how access to synthetic data enables otherwise impossible analysis. First, the question of how synthetic cases may be generated in an automatic manner, and how synthetic samples should be validated to assess whether they are sufficiently ``real'' is considered. Transmission and distribution levels are treated separately, due to the different nature of the two systems. Distribution systems are constructed by sampling distributions observed in a dataset from the Netherlands. For transmission systems, only first-order statistics, such as generator limits or line ratings are sampled statistically. The task of constructing an optimal power flow case from the sample sets is left to an optimization problem built on top of the optimal power flow formulation. Secondly, attention is turned to some examples where synthetic models are used to inform analysis and modeling tasks. Co-simulation of transmission and multiple distribution systems is considered, where distribution feeders are allowed to couple transmission substations. Next, a distribution power flow method is parametrized to better account for losses. Numerical values for the parametrization can be statistically supported thanks to the ability to generate thousands of feeders on command. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2019

Les séismes de type longue période (LP) sont aujourd’hui enregistrés sur la plupart des volcans dans le monde entier. Malgré cela, le mécanisme à leur source n’est encore que très peu compris. A l’heure actuelle les modèles proposés pour expliquer leur origine sont : 1) la résonance d’une fracture remplie de gaz ou de fluides excités par des instabilités dans l’écoulement des fluides ou par la rupture fragile du magma ; 2) la fracturation lente des sédiments peu consolidés à la surface des volcans, dans des conditions de transition entre le ductile et le fragile. L’outil le plus utilisé pour comprendre leur nature est aujourd’hui l’inversion du tenseur des moments. Au cours des dernières années, les inversions du tenseur des moments se concentraient principalement sur la compréhension du mécanisme physique à l’origine des séismes LP qui souvent supposaient des milieux géologiques très simples, voire homogènes. Des études récentes ont montré l’influence des sédiments peu consolidés à la surface des volcans sur la propagation des ondes à basse fréquence et en conséquence, sur l’inversion du tenseur des moments quand ils ne sont pas pris en compte dans le processus d’inversion. Le but de cette thèse est de mieux comprendre les processus physiques qui génèrent les séismes LP et de quantifier les incertitudes liées à leur interprétation. / Long-period (LP) seismic events are abundantly recorded during rest and unrest periods at many volcanoes worldwide. However, their source mechanism is still poorly understood. Models which have been proposed so far to explain their origin are: 1) the resonance of a fluid-filled cavity triggered by fluid instabilities or the brittle failure of magma; 2) slow-rupture earthquakes occurring in the low consolidated materials composing the shallow portion of the volcanic edifice. Nowadays the main tool used to get insights into their nature is moment tensor (MT) inversion. MT inversions carried out in the past years focused mainly on the understanding of the physical origin of LP events and often supposed a relative simple geological structure of the medium. Recent studies highlighted the strong influence of shallow unconsolidated materials on the retrieved MT solutions and the importance of considering geological inhomogeneity in the inversion process. The principal aim of this thesis is to gain a better understanding of the source processes that generate LP events and to quantify the uncertainties related to the MT inversion process.