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

Stock, Adam and Cole, Matthew and Leithead, Bill and Amos, Lindsey; (2020) Distributed control of wind farm power set points to minimise fatigue loads. In: 2020 American Control Conference (ACC). American Control Conference . IEEE, USA, pp. 4843-4848. ISBN 978-1-5386-8266-1 (https://doi.org/10.23919/ACC45564.2020.9147732)

[thumbnail of Stock-etal-ACC-2020-Distributed-control-of-wind-farm-power-set]
Preview
 Text. Filename: Stock_etal_ACC_2020_Distributed_control_of_wind_farm_power_set.pdf
Accepted Author Manuscript
Download (2MB)| Preview

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.

  • Item type:Book Section
    ID code:71210
    Dates:
    Date
    Event
    27 July 2020
    Published
    16 January 2020
    Accepted
    Notes:© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:27 Jan 2020 12:31
    Last modified:11 Nov 2024 15:23
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/71210
CORE (COnnecting REpositories)