| Description |
The continuous growth in energy demand together with the awareness of greenhouse gases and their implication on climate change has pushed our society to design new environmentally sustainable sources of energy. An example of this is the rapid growth that wind and solar energy production has experienced, thanks to the installation of large wind and solar farms. As a result of their large dimensions and their corresponding mechanisms to harvest energy, these energy systems are prone to interact with the atmospheric boundary layer, which is defined as the lowest part of the troposphere that is directly influenced by the presence of the earth surface, and therefore, it directly influences the energy harvesting of large scale wind farms. Hence, understanding the interaction mechanisms between wind farms and the atmospheric boundary layer is of crucial importance to properly determine their optimal performance. Specifically, this work focuses on the development of new understanding regarding wind energy and its interaction with the atmospheric boundary layer, with the main goal to help in developing more efficient wind energy harvesting systems. In detail the objectives of my PhD work are: (i) create new understanding regarding wind turbines' inflow as it relates with time alignment of the turbines; (ii) determine the dominant turbine wake recovery processes under different atmospheric stratification conditions; (iii) develop a useful analytical predictor model to estimate large scale wind farms power output. These objectives will be met through four specific tasks that comprise Chapters 2 to 5 of this dissertation. High-resolution numerical simulations of the atmospheric boundary layer are used in all tasks. |
