PAPERS TO GO FURTHER - Join us!
Below is the list of accepted and submitted papers from our Apogee project Team since 2017.
It should help you have a deeper understand of the challenges we are tackling and yet the approaches we have been exploring. We hope this could give you draw some inspirations to join us make further advances in the field of AI for Smart Grids!
Most of those papers can be found on arxiv and HAL libraries.
Accepted papers 2017 -2019
- IERP 2017: Introducing Machine Learning for power system operation support
- ESANN 2018: Fast Power System Security Analysis with Guided Dropout
- IJCNN 2018: Anticipating contingengies in power grids using fast neural net screening
- ISGT Europe 2018: Optimization of computational budget for power system risk assessment
- ISGT Europe 2018 & NIPS 2019 Workshop: Guided machine learning for power grid segmentation
- MedPower 2018: Expert System for topological remedial action discovery in smart grids
- ESANN 2019: Leap Net for power grid perturbations
- IJCNN 2019: Graph Neural Solvers for Power Systems
- EGC 2019: Semi-supervised labelling, Towards an Extended Expert Approch
- ECML 2019: Interpreting atypical conditions in systems with conditional autoencoder
- Neurocomputing Jounal: LEAP Nets for System Identification and Application to Power Systems
- PSCC 2020: Unsupervised Graph Neural Solver for Power Flow Computation
- PSCC 2020: Learning to run a power network by training topology controllers
Réseau de Transport d'Électricité (Electricity Transmission Network), usually known as RTE, is the electricity transmission system operator of France. It is responsible for the operation, maintenance and development of the French high-voltage transmission system, which at approximately 100,000 kilometres (62,000 mi), is Europe's largest. RTE R&D is one of the strongest in the world in the field of power grids and has many research collaboration around the world, especially in Europe and in the USA. RTE is now a member of the Linux Foundation Energy Initiative in which it open-sourced many simulators and applications.
ChaLearn is a non-profit organization with vast experience in the organization of academic challenges. ChaLearn is interested in all aspects of challenge organization, including data gathering procedures, evaluation protocols, novel challenge scenarios (e.g., competitions), training for challenge organizers, challenge analytics, result dissemination and, ultimately, advancing the state-of-the-art through challenges.