Wind turbines often operate under cold weather conditions where icing may occur. Icing causes the blade sections to stall prematurely reducing the power production at a given wind speed. The unsteady aerodynamic loads associated with icing can accelerate blade structural fatigue and creates safety concerns. In this work, the combined blade element-momentum theory is used to compute the air loads on the baseline rotor blades, prior to icing. At each blade section, a Lagrangian particle trajectory model is used to model the water droplet trajectories and their impact on the blade surface. An extended Messinger model is next used to solve the conservation of mass, momentum, and energy equations in the boundary layer over the surface, and to determine ice accretion rate. Finally, the aerodynamic characteristics of the iced blade sections are estimated using XFOIL, which initiate the next iteration step for the computation of air loads via combined blade element theory. The procedure repeats until a desired exposure time is achieved. The performance degradation is then predicted, based on the aerodynamic characteristics of the final iced blades. The 2-D ice shapes obtained are compared against experimental data at several representative atmospheric conditions with acceptable agreement. The performance of a generic experimental wind turbine rotor exposed to icing climate is simulated to obtain the power loss and identify the critical locations on the blade. The results suggest the outboard of the blade is more prone to ice accumulation causing considerable loss of lift at these sections. Also, the blades operating at a higher pitch are expected to accumulate more ice. The loss in power ranges from 10% to 50% of the rated power for different pitch settings under the same operating conditions.

Nowadays, the energy sector is facing a huge demand that needs to be covered. Wind energy is one of the most promising energy resources as it is free from pollution, clean and probably will arise as one of the main energy sources to prevent global warming from happening. Almost 10% of the global energy demand is coming from renewable resources. By 2050 this percentage is expected to grow to 60%. Therefore, efforts on wind turbine technology (i.e. reliability, design…) need to be coped with this growth. Currently, large wind energy projects are usually carried out in higher altitudes and cold climates. This is because almost all of the cold climates worldwide offer profitable wind power resources and great wind energy potential. Operating with wind turbines in cold climates bring interesting advantages as a result of higher air density and consequently stronger winds (wind power is around 10% higher in the Nordic regions). Not only benefits can be obtained but extreme conditions force to follow harsh conditions. Low temperatures and ice accretion present an important issue to solve as can cause several problems in fatigue loads, the balance of the rotor and aerodynamics, safety risks, turbine performance, among others. As wind energy is growing steadily on icy climates is crucial that wind turbines can be managed efficiently and harmlessly during the time they operate. The collected data for the ice detection, de-icing and anti-icing systems parts was obtained through the company Arvato Bertelsmann and is also based on scientific papers. In addition, computer simulations were performed, involving the creation of a wind tunnel under certain conditions in order to be able to carry out the simulations (1st at 0ºC, 2nd at -10ºC) with the turbine blades rotating in cold regions as a standard operation. In this project, Computational Fluids Dynamics (CFD) simulation on a 5MW wind turbine prototype with ice accretion on the blades to study how CL and CD can change, also different measures of ice detection, deicing and anti-icing systems for avoiding ice accumulation will be discussed. Simulation results showed a logical correlation as expected, increasing the drag force about 5.7% and lowering the lift force 17,5% thus worsening the turbine's efficiency.

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