Decarbonizing Transportation through Electrification

The power and energy system is evolving quickly. The available energy resources are changing, due to the introduction a large share of renewable-based generation sources. This paradigm shift is forcing the involved players to adapt their roles accordingly. The available infrastructure is evolving quickly as well, encompassing the installation of new types of sensors, metering devices, communication channels and control technology. This is enabling the acquisition of a much richer set of data, which is essential to support the decisions required to cope with the needs of the new emerging environment. With the increase of data volume and complexity, learning models must be adapted, and state-of-the art machine learning models, namely in the field of deep learning, are promising solutions to address problems with these characteristics. This panel brings together different views on the state of the art advances that are being reached in the application of deep learning approaches to solve diverse power and energy systems’ problems, such as voltage stability control, smart grid management, energy resources forecasting and synthetic data generation.