Distributed control of wind farm power set points to minimise fatigue loads

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Abstract

The quantity and size of wind farms continue to grow as countries around the world strive to meet ambitious targets for renewable electricity generation such as the UK government's Net Zero target of increasing offshore wind energy from current levels (circa 6 GW) to circa 75 GW by 2050. With increasing size and quantity of wind farms, there is a growing requirement to use wind farm level control both to help with grid integration and to minimise the loads on the turbines in the farm. In this paper, a methodology of distributing power set points through a wind farm to minimise the loads on the turbines whilst meeting a delta power set point for the farm is presented. The methodology in this paper uses a hierarchical control structure, in which a network wind farm controller calculates the required change in wind farm power and then passes this value on to a distributed controller that defines the change in power required from each wind turbine. The network wind farm controller calculates a delta change in wind farm power that the wind farm holds in reserve. The distributed controller allocates the reductions in power output by first setting a baseline reduction that considers the steady state tower loads. The baseline is then adjusted to meet the required change in power, distributing the additional change in one of two ways; either proportional to the square of each turbines estimated wind speed or proportional to the initial baseline. Performance is assessed using the StrathFarm simulation tool. The wind turbine models incorporated into StrathFarm are sufficiently detailed to provide the tower and blade loads and the wind field model is sufficiently detailed to represent turbulence, wind shear, tower shadow and wakes and their interaction. The performance of the proposed wind farm controllers are assessed for a range of wind conditions for two 4x4 wind farms of 5MW wind turbines, one closely spaced (500m) and one less closely spaced (1000m). Both the accuracy of the change in power output from the wind farm and the change in turbines DELs are discussed. Depending on the wind conditions, the approach is found to reduce the tower and blade loads by about 10% more than the case in which each turbine is simply allocated the same change in power. There is good accuracy in the change in power at higher wind speeds. Below rated wind speed, wake effects reduce the accuracy of the change in power.

Original languageEnglish
Title of host publication2020 American Control Conference (ACC)
Place of PublicationPiscataway, N.J.
PublisherIEEE
Pages4843-4848
Number of pages6
ISBN (Electronic)978-1-5386-8266-1
DOIs
Publication statusPublished - 27 Jul 2020
EventAmerican Control Conference (ACC) 2020 - CO, USA, Denver, United States
Duration: 1 Jul 20203 Jul 2020
http://acc2020.a2c2.org/

Publication series

NameAmerican Control Conference
PublisherIEEE
ISSN (Electronic)2387-5861

Conference

ConferenceAmerican Control Conference (ACC) 2020
Abbreviated titleACC
CountryUnited States
CityDenver
Period1/07/203/07/20
Internet address

Keywords

  • wind speed
  • wind power
  • renewable energy

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