The power generated from wind is not synchronized to the electrical frequency of the power grid. Grid balancing services must be assured when the output from a wind farm is integrated into the electrical grid to avoid the risk of blackouts. Active Power Control (APC) methods are employed to provide grid balancing ancillary services such as frequency control. One objective of APC is to have the total power generated from a wind farm, track the power demand requirements obtained from the utility grid. To achieve this objective, the wind farm should be able to operate below their maximum power production capacity i.e, in derating mode. This implies that the turbines in the wind farm should also be derated. The presence of wakes in the wind farm results in the downstream turbines to experience reduced wind speed and increased turbulence.
The earlier works on APC for wind farms revealed the need for a closed-loop wind farm control strategy to combat the effect of wake turbulence. The presence of wakes posed several challenges on obtaining the estimate of the available power at every turbine on a time scale of seconds. Yet, some model-free algorithms were dependent on the estimation of available power at every turbine in the wind farm. This, leads us to the question, “Can a wind farm controller be developed to provide APC for waked wind farms, where the setpoint selection and distribution are made without estimating the available power at each turbine?” To explore the answer to this question, a single wind turbine power tracking control algorithm is developed as the first step. This tracking algorithm does not depend on the estimation of available power. The proposed algorithm makes the turbine operate on two different operating modes namely, the perfect tracking mode and greedy/boosting mode. The algorithms were developed in a way that they can be integrated with the existing torque and pitch controllers of the turbine. Following this, a closed-loop wind farm control strategy has been developed. The closed-loop wind farm controller takes the total power generated from the wind farm as the feedback signal. Based on the operating mode of the individual turbines, the wind farm controller coordinates and distributes the total power reference signal as individual power set-points to the respective wind turbines. The performance of the closed loop wind farm controller was evaluated for a 9-turbine case in SOWFA simulation for four different scenarios. The scenarios differed from each other based on the way the turbines in the wind farm are derated and the individual set points to the turbines are distributed by the wind farm controller. Simulation results showed that the scenario in which the upstream turbines are derated more than the downstream turbines, the tracking performance was better compared to the other scenarios. The damage equivalent loads experienced by the tower base of the individual turbines were also calculated and each of the scenario resulted in different loading patterns. Recommendations are also provided to extend this work and perform further research.

At large oceans depths (5000m) manganese nodules are formed, these are rock shaped objects that contain various rare earth metals, Royal IHC is currently developing equipment to bring these nodules to the shore. The nodules will be transported to the water surface using a Vertical Transport System (VTS).

In the VTS insight of the location of solid concentrations is required: This enables anticipation of the coming flow at the vessel, it is required for controlling the pumps, it will indicate where plugs are likely to be formed and furthermore it will indicate if the aimed production is achieved. For the vertical transport system it has been proposed to measure the volumetric concentration of solids inside the booster stations located every 1000m and predict the propagation of solids in between these measurements, it was found that this configuration has the disadvantage that measurement error in the booster stations results in an error over the whole length of a riser section. An unknown parameter of the slurry flow is the particle diameter, this parameter influences the transport velocity of the solids. These two topics resulted in the following question: "How can the observation of solid concentrations inside a riser be improved?".

In order to evaluate this research question an observer is designed for a scaled test setup of the VTS, on this setup designed improvements will be tested. Started is with an observability analysis, it was found that pressure difference measurements over a large distance of the riser will increase the observability of the system. In order to apply the observer to the test setup it has been investigated how the pressure difference measurements translate into a measured concentration, it was found that the pressure drop created by the wall friction of the mixture can be approximated with liquid wall friction. The Ensemble Kalman Filter was used to observer the concentration through the riser. An addition of the observer is an estimator for the particle diameter: A proposal for this observer is to adapt the particle diameter by using a proportional integral of the lag found between the concentration estimate over a large distance and the concentration measurement at that point.

The observer has been applied to measurements of a scaled riser section of 140m. It was found that by using a pressure difference measurement over the whole section of a riser, the concentration observation at the top of the riser can by significantly improved. Using the observer it has been enabled to distinguish different mixtures. There are errors in the outcome of the particle diameter estimate due to the fact that at the conditions of the test setup were not optimal, however it has been proven that by applying the particle diameter observer an improvement can be seen in the concentration observation. A sensitivity of the observer was found to be the relation of the pressure difference measurement to the wall roughness of the riser, the effect of this parameter needs to be accounted for by periodically re-determining the wall roughness.