Maschinelles Lernen im Energiemanagement

What it is about

The module conveys data-driven prediction and control methods for next-generation energy management systems. You will learn how machine learning techniques are used for load and generation forecasting, system identification, and data-driven control (e.g., model predictive control, Deep Reinforcement Learning) to improve efficiency and the use of renewable energies.

What you will be able to do

• Understand selected techniques of machine learning conceptually and formally
• Understand the application of ML techniques in energy management
• Apply and evaluate machine learning algorithms in selected use cases
• Understand selected methods for data-driven control conceptually and formally
• Apply and evaluate data-driven control in selected use cases
• Reflect on the methods with regard to sustainable ecological, social and economic development
• Develop inter- and transdisciplinary approaches to link ecological, social and economic aspects

What the module consists of

• VorlesungVermittlung der theoretischen Grundlagen zu Vorhersage- und Steuerungstechniken sowie Anwendungen im Energiemanagement
• ÜbungenVertiefung des methodischen Verständnisses und Anwendung der vorgestellten Techniken; Fokus auf methodisches Verständnis statt reiner Programmieraufgaben

Teaching method

• Vorlesung mit praktischen BeispielenIntroduction to concepts and demonstration of applications
• ÜbungenPractice and deepening of the application methods
• Codebeispiele mit Echtdaten / Live-ProgrammierungDemonstration of implementation and application of data-driven methods
• Selbststudium mit digitalen Zeitschriften und BüchernSupplement and deepening of the lecture content