Artificial Intelligence in Smart Energy Systems [COMP-942]


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Course Overview

This course will teach you how to digitalize the “traditional” energy system and how artificial intelligence among the digital technologies can support the planning and operation tasks in the transformed “smart” energy system.

The digital grid operations of the energy system open the door to the use of AI, machine learning, blockchain, and computer simulations. This transition aims to make the energy system more sustainable, economical, accessible, and secure. In addition, there is a growing need that the energy system should support an increasing share of renewable energy, electric transportation, and an integrated approach towards integrated handling of heat and gas infrastructure.

The shift globally has already begun, with more individuals installing solar panels, societal adoption of hybrid vehicles opening the way for electric vehicles, and new technologies such as heat pumps. The primary reason is economic factors, but climate change also plays a significant role.

Why are we hearing more about blackouts, energy shortages, and capacity issues in the energy system these days? Furthermore, how can we use digital technologies like Artificial Intelligence to address such issues?

If you want to find out the answers to these questions, you have come to the right place. This course will teach you about artificial intelligence in smart energy systems, which will help you overcome these obstacles.

This course teaches you about the advantages of a digital grid and the various digital technologies that can be used to realize them. You will see how artificial intelligence and machine learning can improve grid efficiency and autonomy. Human operators are being transformed into supervisors.

We examine numerical simulators, virtual system models, and digital twins, which help analyze the effects of digital technologies in the real world and the application of artificial intelligence technologies, resulting in better decision-making. In addition, you will discover how to protect the grid from cyber-attacks and where it might be vulnerable.

The course is divided into four subject modules, each addressing a distinct aspect of the energy system’s digital transformation:

  • The Energy System’s Digital Transformation
  • Energy Network Computational Methods
  • Integrated Energy System Decision Support
  • AI-Based Data and Machine Learning Methodologies

Goals for learning

This course will teach how digitization will affect the future energy grid. Particularly, you will learn how and where to:

  • Recognize the digital transformation in the energy sector, identify challenges and solutions, and assess the impact on the power system and society
  • To compare the various model types used for numerical simulations of energy systems and to assess the impact of specific parameters and system models on the simulation performance.
  • To explain the various objectives of decision-making in energy systems and the impact of different units and their attributes on decision-making.
  • Using and evaluating artificial intelligence technologies for prediction and control in energy systems.