Abstract

Abstract. This paper studies a closed-loop wind farm control framework for active power control (APC) with a simultaneous reduction of wake-induced structural loads within a fully developed wind farm flow interacting with the atmospheric boundary layer. The main focus is on a classical feedback control, which features a simple control architecture and a practical measurement system that are realizable for real-time control of large wind farms. We demonstrate that the wake-induced structural loading of the downstream turbines can be alleviated, while the wind farm power production follows a reference signal. A closed-loop APC is designed first to improve the power-tracking performance against wake-induced power losses of the downwind turbines. Then, the nonunique solution of APC for the wind farm is exploited for aggregated structural load alleviation. The axial induction factors of the individual wind turbines are considered control inputs to limit the power production of the wind farm or to switch to greedy control when the demand exceeds the power available in the wind. Furthermore, the APC solution domain is enlarged by an adjustment of the power set-points according to the locally available power at the waked wind turbines. Therefore, the controllability of the wind turbines is improved for rejecting the intensified load fluctuations inside the wake. A large-eddy simulation model is employed for resolving the turbulent flow, the wake structures, and its interaction with the atmospheric boundary layer. The applicability and key features of the controller are discussed with a wind farm example consisting of 3×4 turbines with different wake interactions for each row. The performance of the proposed APC is evaluated using the accuracy of the wind farm power tracking and the wake-induced damage equivalent fatigue loads of the towers of the individual wind turbines.

Highlights

  • The number and size of large-scale wind farms are rapidly growing worldwide due to more deployment of wind energy

  • We propose an extension to the active power control (APC) of waked wind farms to actively regulate the distributing set-points, yielding reduced structural loading when the total power production tracks a time-varying power reference, demanded by the transmission system operator (TSO)

  • This section focuses on a simulation scenario in which the wake interactions are problematic for a good wind farm power-tracking performance, similar to Fleming et al (2016), van Wingerden et al (2017), and Vali et al (2018a, b)

Read more

Summary

Introduction

The number and size of large-scale wind farms are rapidly growing worldwide due to more deployment of wind energy. M. Vali et al.: An active power control approach for wake-induced load alleviation turbines, it is possible to influence their wakes, and as a result the performance of downwind turbines, possibly increasing their energy extraction or decreasing their structural fatigue loads. The main contribution of this paper is an extension to the APC approaches proposed in Fleming et al (2016), van Wingerden et al (2017), and Vali et al (2018b) to reduce the structural fatigue loading of the individual wind turbines in a waked wind farm by actively coordinating their power setpoints, the so-called APC with a coordinated load distribution (CLD) law. 2. An effective usage of the locally available wind power at the waked turbines to enlarge the APC solution domain and increase the controllability of the wind turbines for rejecting the intensified structural loading inside the wakes. The strengths and weaknesses of the proposed approach are outlined in Sect. 5 as conclusions of the current study

Wind farm simulation model
The wind turbine model
The case study
Wind turbine controller design
Wind farm controller design
Compensation of accumulated wake-induced power losses
Wake-induced structural load control
Results and discussion
Active power control of waked wind farms
Performance analyses
Baseline open-loop control
Closed-loop APC
Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call