• Muhammad Ali

Student thesis: Phd


Wind power installations have seen a significant rise all over the world in the past decade. Further significant growth is expected in the future. The UK's ambitions for offshore wind installations are reflected through Round 1, 2 and 3 projects. It is expected that Round 3 alone will add at least 25 GW of offshore wind generation into the system. Current research knowledge is mostly limited to smaller wind farms, the aim of this research is to improve offline and online modelling techniques for large offshore wind farms. A critical part of offline modelling is the design of the wind farm. Design of large wind farms particularly requires careful consideration as high capital costs are involved. This thesis develops a novel methodology which leads to a cost-effective and reliable design of an offshore wind farm. A new industrial-grade software tool is also developed during this research. The tool enables multiple offshore wind farm design options to be built and tested quickly with minimal effort using a Graphical User Interface (GUI). The GUI is designed to facilitate data input and presentation of the results.This thesis also develops an improved method to estimate a wind farm's energy yield. Countries with large-scale penetration of wind farms often carry out wind energy curtailments. Prior knowledge of estimated energy curtailments from a wind farm can be advantageous to the wind farm owner. An original method to calculate potential wind energy curtailment is proposed. In order to perform wind energy curtailments a network operator needs to decide which turbines to shut down. This thesis develops a novel method to identify turbines inside a wind farm that should be prioritised for shut down and given priority when scheduling preventive maintenance of the wind farm. Once the wind farm has been built and connected to the network, it operates as part of a power system. Real-time online simulation techniques are gaining popularity among system operators. These techniques allow operators to carry out simulations using short-term forecasted wind conditions. A novel method is proposed to probabilistically estimate the power production of a wind farm in real-time, taking into account variation in wind speed and effects of turbulence inside the wind farm. Furthermore, a new probabilistic aggregation technique is proposed to establish a dynamic equivalent model of a wind farm. It determines the equivalent number and parameters of wind turbines that can be used to simulate the dynamic response of the wind farm throughout the year.
Date of Award31 Dec 2012
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorJovica Milanovic (Supervisor)


  • probabilistic
  • methodology
  • electrical losses
  • reliability
  • curtailment
  • energy yield
  • wind power
  • critical wind turbines
  • loss calculation
  • wind farm
  • wake effect
  • transient stability
  • aggregate model
  • cost benefit
  • robust design
  • wind turbine
  • dynamic equivalent

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