Advanced algorithms for forecasting renewable electricity generation

KU Leuven , 1 or 2 semesters
Taking the grid operator’s perspective, the student will implement cutting-edge forecasting algorithms for renewable electricity generation.
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Advanced algorithms for forecasting renewable electricity generation
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In this project, the student will investigate different algorithms to create forecast models for renewable electricity generation. More concretely, the student will incorporate two important factors in the analysis:

  1. how can uncertainties in the forecast be effectively quantified, and
  2. how can spatial hierarchies be preserved while making these forecasts.

Forecasting renewable electricity generation accurately is an increasingly important challenge. Currently forecast errors are scaling linearly with installed capacity - a situation which is clearly not tenable in the long run. This means that uncertainties in forecasts must be clearly quantified and communicated to all important stakeholders. Likewise, incorporating hierarchical aspects is an important topic as uncertainties vary considerably across production source and location (i.e. simply adding uncertainty estimates in region 1 and region 2 will not produce correct overall uncertainty estimates).

Number of placements available: 1 per semester.

Prerequisites

  • High level (3rd / 4th year) undergraduate student 
  • Minimum GPA 3.4
  • Familiarity with Python programming langauge.
  • Some knowledge of forecasting and/or machine learning is highly encouraged.

Important note: 

Students must remain registered as an undergraduate student at their U.S. or Canadian home institution while participating in the program. The student's home institution must complete the Learning Agreement after acceptance into a project, even if credits will not be transferred to that institution. Transfer of credits is decided by the students' home institution.

Submitting an application, does not guarantee that the student will be offered a placement. The research projects are also available to our domestic degree students; therefore, projects may already be full at the time of applying. Final decision on your admission is solely taken by the Research Supervisor at the host institution.

Faculty Department

Electrical Engineering

The research domain of the ELECTA division covers the broad spectrum of electrical energy systems and robust control of industrial systems. As the largest research group on energy systems and fault tolerance in the Benelux, ELECTA's vision is to be widely recognized as centre-of-excellence on these topics, where fundamental research is coupled with immediately and prospectively applicable solutions for the industry. Alongside this development of know-how, a pivotal importance is given to sharing gained knowledge with the academic community, students, industry and the society as a whole.