While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that th ...
Hydropower plants play a crucial role in the power system facing ambitious renewable energy targets. Due to their inherent controllability, they are well suited to provide flexibility to the grid. However, an increased flexibility provision leads to a prol ...
According to the International Energy Agency, the global net-zero emissions objective requires the installed wind power capacity to increase 11-fold between 2020 and 2050. The scientific community has recently voiced concerns about the logistic feasibility ...
Large Eddy Simulations (LES) of atmospheric boundary layer (ABL) flow with the actuator disc (AD) for turbine modelling is a widely used method of simulating wind farm flows. Hence, it is important to understand the requirements for achieving a good compar ...
In this thesis, we explore the best practice of simulating the wakes of the turbines under active yaw control (AYC) using large-eddy simulation (LES). In the first study, we validate the blade-element actuator disk model (ADM-BE) for a yawed wind turbine. ...
Risk management has become an essential element in the functioning of modern society. Correct risk identification and assessment are undoubtedly crucial to improving overall safety; nevertheless, often, it is accompanied by the wrong selection of correctiv ...
This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions ...
