Wind turbines offer an appealing method for power generation. In the fight against global warming wind energy helps realise green house gas emission reduction targets. Moreover, given a globally increasing demand for energy, the role of wind energy is set to become even more important. Historically, the cost of wind energy has decreased significantly, making it more competitive with respect to fossil fuels. This trend is set to continue thanks in part to a driving factor, which is the increasing size of wind turbines. However, there are several impediments to the upscaling of wind turbine sizes. The larger, more flexible wind turbine components experience greater loads. To mitigate increasing fatigue loading, which limits the lifetime of components, thereby increasing the cost of wind energy, smart control methodologies are needed. The existing literature indicates that individual pitch control (IPC) offers good perspectives for fatigue load mitigation. An interesting approach to performing IPC is by means of model predictive control (MPC). Unlike conventional IPC implementations, MPC offers the designer a more intuitive way to evaluate trade-offs between, e.g., power generation and load mitigation. In addition, an important advantage of MPC is its ability to handle constraints explicitly. A particularly interesting application of MPC for wind turbine operation concerns convex economic model predictive control (CEMPC). By means of a simple change of variables, the normally troublesome nonlinear dynamics are transformed into linear dynamics. As a result, relevant optimization problems can be reformulated in a convex fashion. The formulation of such a convex optimization problem is useful because such problems enable a global optimum to be found, and can be solved relatively efficiently. Unfortunately, the existing CEMPC framework is limited to collective pitch control (CPC). To facilitate further load reduction, it would be useful to extend the CEMPC framework to the domain of IPC. This thesis therefore seeks to investigate how the existing CEMPC framework can be extended to the domain of IPC for the purpose of wind turbine load mitigation. It is shown that an improved CPC implementation of CEMPC can be extended to IPC by considering a blade-effective wind speed and CPC-equivalent aerodynamic power for each blade. With regards to load reduction, a case study of out-of-plane blade root bending moment fatigue load mitigation indicates several important difficulties that require further investigation. Arguably the most important impediment for future load reduction prospects within CEMPC using IPC is the inability to consider the pitch, which is an important variable to minimize various sorts of loading, as a free optimization variable.