Open thesis topics

Analysis of dataset for energy forecasting

Keywords: RES, energy forecasting, training dataset, testing dataset,  prediction error

Description and objectives:

Integration of Renewable energy resources (RES) in today's power grid depends highly on the quality of energy forecasting outcome. However, the variability of RES poses several challenges to this integration. The idea of the proposed thesis is to assess the influence of different dataset composition which includes varying training, validation and testing dataset on the prediction error and to come up with the most effective training method. The performance of the training method will be validated over publicly available dataset using available performance evaluation metrics.

Main tasks:

• The first task is to look for dataset having different characteristics in order to achieve better comparison and assessment of most effective approach when applied to different datasets.
• The next task is to train neural network using machine learning algorithms for different dataset composition. 

Qualifications: Programming skills in Python

Contact Details:  Ekanki SHARMA : Ekanki.Sharma@aau.at 

Impact of data pre-processing techniques on forecasting accuracy

Keywords: RES, data pre-processing, energy forecasting, feature selection, outlier rejection, forecasting accuracy

Description and objectives:

To integrate renewable energy sources (RES) in power grid, forecasting the photovoltaic (PV) yield is very important. Several techniques have been implemented in the literature which includes naive (time-series, statistical) methods to soft computing techniques (Artificial neural network, support vector machine, grey prediction) to improve the accuracy of the forecasting model. The idea of the thesis is to evaluate the impact of applying feature selection and outlier rejection techniques on forecasting accuracy. 

Main tasks:

• The first task is to search for available pre-processing techniques.
• The next step is to compare the forecast accuracy with and without applying data pre-processing techniques.

Qualifications: Programming skills in python

Contact Details:  Ekanki SHARMA : Ekanki.Sharma@aau.at