Cette thèse porte sur les problèmes de sécurité sur le réseau électrique français exploité par RTE, le Gestionnaire de Réseau de Transport (GRT). Les progrès en matière d'énergie durable, d'efficacité du marché de l'électricité ou de nouveaux modes de consommation poussent les GRT à exploiter le réseau plus près de ses limites de sécurité. Pour ce faire, il est essentiel de rendre le réseau plus "intelligent". Pour s'attaquer à ce problème, ce travail explore les avantages des réseaux neuronaux artificiels. Nous proposons de nouveaux algorithmes et architectures d'apprentissage profond pour aider les opérateurs humains (dispatcheurs) à prendre des décisions que nous appelons " guided dropout ". Ceci permet de prévoir les flux électriques consécutifs à une modification volontaire ou accidentelle du réseau. Pour se faire, les données continues (productions et consommations) sont introduites de manière standard, via une couche d'entrée au réseau neuronal, tandis que les données discrètes (topologies du réseau électrique) sont encodées directement dans l'architecture réseau neuronal. L’architecture est modifiée dynamiquement en fonction de la topologie du réseau électrique en activant ou désactivant des unités cachées. Le principal avantage de cette technique réside dans sa capacité à prédire les flux même pour des topologies de réseau inédites. Le "guided dropout" atteint une précision élevée (jusqu'à 99% de précision pour les prévisions de débit) tout en allant 300 fois plus vite que des simulateurs de grille physiques basés sur les lois de Kirchoff, même pour des topologies jamais vues, sans connaissance détaillée de la structure de la grille. Nous avons également montré que le "guided dropout" peut être utilisé pour classer par ordre de gravité des évènements pouvant survenir. Dans cette application, nous avons démontré que notre algorithme permet d'obtenir le même risque que les politiques actuellement mises en œuvre tout en n'exigeant que 2 % du budget informatique. Le classement reste pertinent, même pour des cas de réseau jamais vus auparavant, et peut être utilisé pour avoir une estimation globale de la sécurité globale du réseau électrique. / This thesis addresses problems of security in the French grid operated by RTE, the French ``Transmission System Operator'' (TSO). Progress in sustainable energy, electricity market efficiency, or novel consumption patterns push TSO's to operate the grid closer to its security limits. To this end, it is essential to make the grid ``smarter''. To tackle this issue, this work explores the benefits of artificial neural networks. We propose novel deep learning algorithms and architectures to assist the decisions of human operators (TSO dispatchers) that we called “guided dropout”. This allows the predictions on power flows following of a grid willful or accidental modification. This is tackled by separating the different inputs: continuous data (productions and consumptions) are introduced in a standard way, via a neural network input layer while discrete data (grid topologies) are encoded directly in the neural network architecture. This architecture is dynamically modified based on the power grid topology by switching on or off the activation of hidden units. The main advantage of this technique lies in its ability to predict the flows even for previously unseen grid topologies. The "guided dropout" achieves a high accuracy (up to 99% of precision for flow predictions) with a 300 times speedup compared to physical grid simulators based on Kirchoff's laws even for unseen contingencies, without detailed knowledge of the grid structure. We also showed that guided dropout can be used to rank contingencies that might occur in the order of severity. In this application, we demonstrated that our algorithm obtains the same risk as currently implemented policies while requiring only 2% of today's computational budget. The ranking remains relevant even handling grid cases never seen before, and can be used to have an overall estimation of the global security of the power grid.

The way its future power systems are designed will have significant impact on sub-Saharan Africa's (SSA) aspirations to move from low electricity consumption rates to enhance life quality and further increase economic opportunity. At present, Africa is experiencing higher economic growth rates than other continents (including Asia). And so is its need for electric power. However, all too often the options that are chosen are the ones with lowest risk and that require little coordination. In part, this is because region-wide planning, coordination and institutions are in their infancy. “Low risk” power plants typically include oil generators that can be sited close to loads, other fossil fuel power plants, and hydro plants that can easily be connected to the continent’s grid. However, hydropower production has been limited due to changes in weather and climate and socio-economic impacts. Additionally, its potential has also not been reached as large sites are far from adequate grids. A restructuring of the energy system that considers both the potential for increased geographical integration while moving gradually towards more sustainable electricity generation may hold significant promise. This work considers the potential of another renewable technology namely concentrating solar power (CSP) and connecting supply and demand centers via high voltage direct current (HVDC) power lines. Specifically, the focus is on utility-scale solar power generation to supply the needs of growing urban centers of demand. It develops a Geographic Information System-based (GIS) model with a spatial resolution of 30 arc-seconds to calculate the cost evolution of the electricity produced by different technologies of CSP plants and the costs of grid development to selected centers of demand. The results show that major SSA metropolis can benefit from distant CSP economically attractive to compete with inlaid coal-based generation. In 2010, total imports of coal exceeded 1.4 million short tons with consequent economic and environmental costs. Solar towers plants endowed with thermal storage may become a leading technology for smoothing purposes with zero fuel costs. Furthermore, Africa’s vast solar resources are far from urban centers of demand and a transmission system capable to integrate high levels of renewable energy while improving reliability of supply is required. The results of this study point to the importance of SSA centers to rely on a Super Grid approach to take advantage from CSP least-cost potential and to discontinue expensive traditional sources. Overall, solar corridors can integrate with geographically-wide wind and hydro potentials to create clean energy corridors and encourage a transition towards more sustainable energy systems.

In this report, we study how finite differences can be used to simulate acoustic wave propagation originating from a point source in the ocean using the Helmholtz equation. How to model sediment layers and the vast size of the ocean is studied in particular. The finite differences are implemented with summation by parts operators with boundary conditions enforced with simultaneous approximation terms and projection. The numerical solver is combined with the WaveHoltz method to improve the performance. Sediment layers are handled with interface conditions and the domain is artificially expanded using absorbing layers. The absorbing layer is implemented with an alternative approach to the super-grid method where the domain expansion is accomplished by altering the wave speed rather than with coordinate transformations. To isolate these issues, other parameters such as variations in the ocean floor are neglected. With this simplification, cylindrical coordinates are used and the angular variation is assumed to be zero. This reduces the problem to a quasi-three-dimensional system. We study how the parameters of the alternative absorbing layer approach affect its quality. The numerical solver is verified on several test cases and appears to work according to theory. Finally, a semi-realistic simulation is carried out and the solution seems correct in this setting.