Evaluation of missing capacity and resource adequacy in an interconnected power system

The uncertainties of the current power system with a larger share of renewables and more volatile generation profiles increases the importance of assessing resource adequacy. Within this framework, the thesis “Evaluation of missing capacity and resource adequacy in an interconnected power system” aims to answer the following question: “How to...

Investigation of active learning techniques for dynamic Time-of-Use (dToU) tariff policy design for residential users

The active learning approach is a special case of semi-supervised machine learning which is able to interactively query the user to reduce the uncertainty of the machine learning model. The approach is useful to minimize the data labeling cost. The project aims to study and use this method to characterize residential electricity users’ demand...

Linear state estimation method for distribution grids

The recent trend for monitoring and control of the distribution networks requires methods capable to calculate the network’s operating conditions. One way to monitor the distribution network is by state estimation. Although previously this method was established only for the transmission networks, its use has begun to also make sense for the...

Urban building energy modeling using a 3D city model and minimizing uncertainty through Bayesian inference: A case study focuses on Amsterdam residential heating demand simulation

To cut down immense greenhouse gases emission and energy consumption in the rapidly urbanizing world, a holistic understanding and rethinking of our dynamic urban energy system are inevitable. Performing bottom-up building energy modelings at urban scale based on Geographic Information System (GIS) and semantic 3D city models could be a...