Thesis

Wind farm control and modelling to provide grid primary response and meet O&M requirements

Creator
Rights statement
Awarding institution
  • University of Strathclyde
Date of award
  • 2019
Thesis identifier
  • T15267
Person Identifier (Local)
  • 201294197
Qualification Level
Qualification Name
Department, School or Faculty
Abstract
  • In the past years, investing in wind industry has been of a great interest. In all future energy scenarios regarding GB power generation, a substantial penetration of wind energy is envisaged. However, at present, except for occasional curtailment of generation, wind farms simply output all the power that can be extracted from the wind at any given time. By increasing the proportion of energy production from wind farms, and especially offshore wind farms, it is of great importance not to operate wind farms in such a simple manner. There is a need of allowing wind farms to operate in a far more flexible way. Regarding the viewpoint of the grid operators, wind farms will need to provide services such as frequency support to match supply and demand. From the viewpoint of the wind farm operators, wind farms will need to be operated in such a manner as to maximise the return of investment. To meet these grid and operator requirements a wind farm controller is developed. The main goal of this thesis is to create a complete power system model to explore whether a wind farm level controller can be utilised to provide ancillary services to the transmission system operator, whilst safe-guarding the wind farm assets. Results from each chapter are novel and provide some new insight towards reducing O&M costs for wind farm operators, while providing advanced flexibility and frequency stability services to the transmission system operator. The thesis concludes that the wind farm controller would be essential for increasing controllability and flexibility of wind farms and improve power system frequency stability.
Advisor / supervisor
  • Leithead, William.
Resource Type
DOI
Date Created
  • 2019
Former identifier
  • 9912708091602996

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