PhD defence by Kuichao Ma


01.07.2021 kl. 12.30 - 15.30


Kuichao Ma, Department of Energy Technology, will defend the thesis "Wind Farm Control under Generator Faults"


Wind Farm Control under Generator Faults


Kuichao Ma


Associate Professor Mohsen Soltani


Professor Zhe Chen


Associate Professor Amin Hajizadeh


Associate Professor Zhenyu Yang, Aalborg University (Chairman)
Professor Dr.-Ing. Horst Schulte, University of Applied Sciences Berlin
Associate Professor Christoffer Sloth, University of Southern Denmark


Nowadays, the development trend of wind energy has changed from distributed to large-scale wind farms and from onshore to offshore. The special environment of offshore wind energy makes the operation of wind turbines facing more serious challenges than that of onshore wind energy. One of them is the high generator fault rate. The humidity at sea makes the generator failure rate much higher. The maintenance costs of the generator are also high because offshore maintenance usually needs special equipment, such as service vessels. Offshore maintenance is also limited by weather condition, such as wind and wave. At the same time, offshore wind turbines generally have a larger capacity. So the power loss caused by the same downtime is more massive. The wake effect is also a factor that offshore wind farms have to consider. 
To solve the problems mentioned above, this thesis studies the control and optimization of offshore wind farms with Doubly-Fed Induction Generator (DFIG)-based wind turbines under generator faults. The objectives include three points: protection of the faulty generator, reduction of the power loss caused by fault, and the optimization of wind farm power. The specific methods are implemented both at the turbine level and the farm level. 
The generator faults studied in this thesis include generator cooling system fault and inter-turn short-circuit fault in stator windings. The common feature of these two types of faults is that they are both heat-related. The impact of these two heat-related faults is not very serious at the initial stage. However, ignoring the fault will lead to further deterioration of the fault. Therefore, this thesis adopts derating strategies to protect the faulty wind turbine and avoid excessive power loss compared with shut-down. 
The contribution of this thesis is to propose reasonable strategies at the turbine level and the farm level for reducing the impact of generator fault on the wind turbine and wind farm, thereby improving the fault operation capability of wind turbines and reducing the Operation \& Maintenance costs of wind farms.
At the turbine level, there are two ways to derate the power of the faulty wind turbine. One is that the faulty wind turbine reduces the faulty phase current through the proposed inter-turn short-circuit fault ride-through strategy. The other is to down-regulate the faulty wind turbine according to the power reference from the wind farm controller. The reference of the faulty wind turbine can not exceed the power limitation calculated by fault model.
At the farm level, particle swarm optimization algorithm is used to optimize the power references of all the wind turbines within the wind farm according to the wind condition, the health condition of the wind turbine and the power demand from the transmission system operator. Furthermore, the down-regulation strategy also has a significant impact on the operating status of the wind turbine and the wind farm. The selection of the specific strategy is based on the health condition of the wind turbine as well. The active power dispatch optimization can reduce the power loss caused by faulty wind turbines and improve the total power while ensuring the safety of the faulty wind turbine.



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Department of Energy Technology


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