Advanced System Technology branch AST of Fraunhofer IOSB
Advanced System Technology branch AST of Fraunhofer IOSB

»Energy Data Science for Optimization«

Continuing education: ‘Energy Data Science for Optimisation’

This seminar provides an introduction to optimising cross-sector energy planning and enables participants to learn these fundamentals through simple examples. Although the seminar is thematically linked to the Energy Data Analyst seminar, it does not build upon it.

In this seminar, participants will learn the fundamentals of mathematical optimisation and discover how optimisation methods can be used to great effect in the energy sector’s planning process. Practical experience is gained through initial exercises that demonstrate how optimisation models can be applied in the energy sector to explore relevant topics such as cross-sector energy planning, the design of an optimal technology mix, and charging management for electric vehicles. Furthermore, the seminar provides insights into current research topics in this field.

By the end of the seminar, participants will be able to identify areas for improvement within their organisation and implement changes, as they will have gained a deeper understanding of the subject matter and the knowledge acquired. 

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OVERVIEW
Format
Online or in Person
Graduation
Certificate of attendance
access Requirements
No special requirements are necessary
Dates, registration deadline and location
  • 25.11. - 26.11.2026 in München (Anmeldefrist: 09.11.2026)
Duration
→ Day 1 – Face-to-face session → Day 2 – Face-to-face session
Language
German
Price
→ €1,950 → If you book this ‘Energy Data Science for Optimisation’ seminar in combination with the ‘Energy Data Analyst’ seminar, you can attend both seminars for the promotional price of €3,700.
More infos
  • The number of participants is limited to 15 per session
TARGET GROUP

Das Seminar »Energy Data Science for Optimization« richtet sich an: Ingenieurinnen und Ingenieure, Mitarbeitende aus Geschäftsführung, Portfoliomanagement, Trading, Energieinformatik, Beschaffung, Vertrieb, Kraftwerkeinsatzplanung, Netzbetrieb oder Energiedatenmanagement aus den Branchen: Energieversorgungs- und Energiedienstleistungsunternehmen, Stadtwerke, energieintensive Industrie und Unternehmensberatungen.

CONTENT AND EXPIRATION

Are you interested in the application of optimisation methods in the energy sector? Would you like to learn how to model and solve complex problems in this field? Then the ‘Energy Data Science for Optimisation’ course is just the thing for you!

In this training course, you will learn:

  • Fundamentals of the Energy Industry with a focus on optimisation

You will learn about the challenges and opportunities in this sector, gain an overview of how energy markets work, and discover the role that optimisation plays in this context.

  • Fundamentals of optimisation

You will acquire the necessary mathematical and algorithmic knowledge to formulate and analyse optimisation problems. You will learn about key terms and concepts such as objective functions, constraints and optimality, and gain an overview of common problem classes and appropriate solution methods.

  • Modelling techniques

You will learn how to translate real-world problems from the energy sector into optimisation models. In doing so, you will gradually learn how to formulate optimisation problems in verbal and mathematical terms, as well as using Pyomo, a free, Python-based modelling language.

  • Exact solution methods

You will learn how to solve optimisation models using specialised solvers. You will understand how various solution algorithms work and their limitations, such as the Simplex algorithm, the branch-and-bound method and the cutting-plane method.

  • Heuristics

You will learn how to solve optimisation problems using simple or advanced heuristics when exact methods are too slow or impractical.

  • Stochastic and robust optimisation

You will learn how to formulate optimisation models that take account of uncertainties and risks. A practical example will be used to illustrate the differences between robust and stochastic optimisation approaches.

  • Current research topics

You will learn about topics related to optimisation from the current research landscape.


The course is designed to be interactive and is divided into self-study, classroom-based and practical components. In the practical section, you will apply the knowledge you have gained on optimisation in the energy sector using the CoCalc course platform to solve real-world problems, whilst creating your own models in Pyomo. You will benefit from the experience and feedback of qualified lecturers and from the exchange with other participants. Register now and secure your place!

Beispielbilder unseres Schulungstools "cocalc"
Beispielbilder unseres Schulungstools "ILIAS"
THE BENEFITS FOR YOU
  • Knowledge of the latest findings from Fraunhofer research and methods relating to time-series forecasting, optimisation and the energy sector
  • Practical knowledge transfer through hands-on exercises
  • Use of various methods from the energy sector and evaluation of the results
  • Immediate applicability of what has been learnt in everyday working life
  • Provision of learning materials on the topics covered
  • Exchange of experiences between participants and Fraunhofer experts in a pleasant learning environment
FURTHER INFORMATION

Further information on the “Energy Data Scientist” seminar series is available here.

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