Summer School: Time Series Analysis - with a focus on modelling and forecasting in energy systems - Technical University of Denmark
26 April 2023
The Technical University of Denmark is organizing a Summer School in partnership with several projects (syn.ikia, ARV, EBC, FME ZEN) and involvement of EXCESS partners. The course will take place from August 14-18, 2023 in Fredericia Region, Denmark (exact location to be announced and shared with all registered participants for booking accommodation in due time).
Registration is mandatory before June 15., see below. More information can be found here.
To integrate renewable and fluctuating power generation sources we need to model, forecast and optimize the operation of distributed energy resources, hence we need self tuning models for each component in the system. E.g. for a building with PV and a heat pump, one will need a model from weather forecasts and control variables to PV power, heat pump load and the indoor temperature in the building. These, together with electricity prices, can then be used for MPC of the heat pump to shift its load to match the generation of power. There are many other applications of data-driven models, eg. performance assessment, flexibility characterization, and fault-detection; these topics will also be presented. The statistical techniques behind the models will be elaborated, with focus on non-parametric (e.g. kernels and splines) models, discrete and continuous time models (grey-box modelling with SDEs).
We will use R and provide exercises to get a “hands-on” experience with the techniques. The summer school will be held for the sixth time by DTU, this time in Fredericia. PhD students completing the course will achieve 2.5 ECTS points. There will be a fee of 250 Euros for participating (higher for industry participants). A social event and dinner is included. We offer no online participation.
A student who has met the learning objectives of the course will be able to:
- Achieve a thorough understanding of maximum likelihood estimation techniques.
- Formulate and apply non-parametric models using kernel functions and splines – with a focus on solar and occupancy effects.
- Formulate and apply time adaptive models.
- Formulate and apply models for short-term forecasting in energy systems, e.g. for heat load in buildings, electrical power from PV and wind systems.
- Application of statistical model selection techniques (AIC, BIC, likelihood-ratio tests, model validation).
- Formulate and apply grey-box and digital twin models – model identification – tests for model order and model validation, and advanced non-linear models.
- Achieve an understanding of model predictive control (MPC) – via applied examples on energy systems.
- Achieve an understanding of flexibility functions and indices.
Register by following the steps depending on your affiliation:
- Master and PhD students from DTU: Sign up for the course 02960 as usual through the study planner
Send a mail to email@example.com informing that you signed up
- PhD students, Postdoc or other university participants not from DTU:Sign up for the summer school at conferencemanager, Choose your affiliation, Follow all steps and pay with a credit card
- Industry participants: Sign up for the course at DTU: Open_universityFill only * marked fields; In “Type of course”: Open University; In “I am signing up for courses in the following period”: Doesn’t matter, August is not even included, In “Course number and title (1)”: 02960 Time Series Analysis – with a focus on Modelling and Forecasting in Energy Systems, You will be charged an additional (appr.) 1000 Euros by DTU for the participation, Sign up for the summer school through conferencemanager, Choose: Industry, Follow all steps and pay with a credit card
- Master students from Danish and Non-Danish universities:Send a mail to firstname.lastname@example.org informing that you wish to sign up
The summer school is held by DTU in a collaboration with Center Denmark, Maskinmesterskolen, NTNU, and IEA EBC Annexes 81, 82 and 83, and the projects FED, ARV, syn.ikia and Elexia. For more information, contact Henrik Madsen (email@example.com) or Peder Bacher (firstname.lastname@example.org). See also this description DTU course 02960.
More information can also be found here.