Master thesis idea in Computing Science or PPRE

Motivation

Nowadays, renewable energy sources, small-scale generation units, and electrical energy storage systems are strongly promoted. Consequently, the use of decentralized energy resources (DERs), which includes all of them, is increasing, and it imposes considerable uncertainties on the operation of smart grids. Therefore, the probabilistic analysis of smart grids with high penetration of DERs is one of the current hot research topics. However, in most studies and proposed models, an individual probabilistic modeling approach is considered, while the DERs (such as wind turbines and PV units) are inherently temporally and spatially correlated to each other and not considering the correlations would lead to unrealistic modeling of the system. Therefore, it is necessary to propose a multivariate uncertainty modeling based on the correlation approach for more accurate and efficient operation of smart grids.

Objective

The aim of this thesis is to propose a multi-dimensional uncertainty model between DERs. Since the number of DERs is high in smart grids, the dimension of the model will be increased, and finding a mathematical solution will be complicated. The Copula function is one of those solutions that is able to decouple the problem into solvable terms. The goal of this thesis is to develop an uncertainty model for DERs, using Copula functions to model the correlations.

Profile

The thesis aims at students of computing science, PPRE, physics, or comparable courses of study who are interested in dealing with Theoritical studies, mathematical modeling, spatial statistics, and data science in the field of energy informatics. Previous knowledge in the area of renewable energies, power systems, and Python programming is desirable. The applicant should be willing to deal with the new topic in a motivated and independent way.

 

Contact

Payam Teimourzadeh Baboli

OFFIS – Institute for Infirmation Technologies

Escherweg 2, 26121 Oldenburg

payam.teimourzadehbaboli@offis.de

References

[1]   Project Homepage: https://www.offis.de/en/offis/project/sined.html

[2]   P. Teimourzadeh Baboli, M. Brand and S. Lehnhoff, "Stochastic Correlation Modelling of Renewable Energy Sources for Provision of Ancillary Services using Multi-dimensional Copula Functions," 2021 11th Smart Grid Conference (SGC), 2021, pp. 1-6.
https://ieeexplore.ieee.org/document/9664161       

[3]   Czado C, Nagler T. Vine copula based modeling. Annual Review of Statistics and Its Application. 2021;9.
https://www.annualreviews.org/doi/abs/10.1146/annurev-statistics-040220-101153