Name im Diploma Supplement

Energy Forecasting Competition

Anbieter

Lehrstuhl für Data Science in Energy and Environment

Lehrperson

Prof. Dr. Florian Ziel

SWS

4

Sprache

englisch

Turnus

unregelmäßig

maximale Hörerschaft

unbeschränkt

Hörerschaft

• BWL EaFWahlpflichtbereich 1.-3. FS, Wahlpflicht, Modul Energy Forecasting Competition
• ECMXWahlpflichtbereichME5 Economics 1.-3. FS, Wahlpflicht, Modul Energy Forecasting Competition
• GOEMIKWahlpflichtbereich Bereich Betriebswirtschaftslehre 1.-3. FS, Wahlpflicht, Modul Energy Forecasting Competition
• MuUWahlpflichtbereich IIWahlpflichtbereich II B.: Märkte und Unternehmen aus Marktperspektive 1.-3. FS, Wahlpflicht, Modul Energy Forecasting Competition
• VWLWahlpflichtbereich II 1.-3. FS, Wahlpflicht, Modul Energy Forecasting Competition

empfohlenes Vorwissen

Basics in R or python, basics in data science or statistics.

Abstract

In the first third of the Module the students study the competition design, the forecast evaluation methods, benchmark methods and forecasting principles in general in a lecture. The competition task and the corresponding data sets will be released immediately. In the second part the student construct their own forecasting model for the competition and submit their forecasts. Shortly afterwards the results will be released. In the third part of the students write a report on the prediction methods and present their finding.

Lehrinhalte

1. Introduction on forecasting competitions
2. Competition design and reporting of forecasts
3. Evaluation metrics
4. Benchmark methods
5. Options for improving forecasts

Literaturangaben

• Hong, T., Pinson, P., Fan, S., Zareipour, H., Troccoli, A., & Hyndman, R. J. (2016). Probabilistic energy forecasting: Global energy forecasting competition 2014 and beyond.  International Journal of Forecasting, 32(3), 896-913.
• Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2020). The M4 Competition: 100,000 time series and 61 forecasting methods. International Journal of Forecasting, 36(1), 54-74.
• Further Literature will be mentioned during the lecture.

didaktisches Konzept

Classic lectures + Learning by doing

Die Veranstaltung entspricht einem Vorlesungsanteil von 2 SWS und einem Seminaranteil von 2 SWS.