Course Description: This course aims teach you how to digitalize the ‘conventional’ energy system and which digital technologies plays a key role. The digitized grid operations then open ways of the application of AI, machine learning, blockchain and computer simulations. The objective of this transformation is to make the energy system sustainable, affordable, available, and secure. This course teaches about the opportunities of a digital grid and the various digital technologies to achieve this. The course consists of an introductory and four-course content modules, each touching upon a different facet of the digital transformation and application of artificial intelligence in the energy system: • The Digital Transformation of the Energy System • Computational Methods for Energy Networks • Decision Support in Integrated Energy Systems • AI-Based Data and Machine Learning Approaches

Course Objectives:

In this course, students will learn: • To recognize the digital transformation in the energy sector, identify challenges and solutions, and evaluate its impact on both the power system and society itself. • To compare the different model types used for numerical simulations of energy systems and evaluate the influence of individual parameters and system models on the simulation performance. • To explain the different objectives of decision-making in energy systems, and the influence of different units and their properties on the decision making. • To apply and evaluate machine learning methods for prediction and control in energy systems