Combined wind turbine fatigue and ultimate load reduction by individual blade control

If each blade of the wind turbine has individual pitch actuator, there is possibility of employing the pitch system to mitigate structural loads through advanced control methods. Previously, considerable reduction of blade lifetime equivalent fatigue loads has been achieved by Individual Blade Control (IBC) and in addition, it has also been shown the potential in blade ultimate loads reduction. However, both fatigue and ultimate loads impact on the design and life of wind turbine blades. In this paper, the design and application of IBC that concurrently reduce both blade fatigue and ultimate loads is investigated. The contributions of blade load spectral components, which are 1P, 2P and edgewise mode from blade in-plane and/or out-of-plane bending moments, are firstly explored. Four different control options for reducing various combinations of these load components are compared. In response to the different spectral peaks of both fatigue and ultimate loads, the controller has been designed so that it can act on different frequency components which vary with wind speed. The performance of the IBC controller on fatigue and ultimate load reduction is assessed by simulating a 5MW exemplar wind turbine. Simulation results show that with a proper selection of controlling inputs at different wind speed, the use of a single combined IBC can achieve satisfactory reduction on both fatigue and ultimate loads

Reduction of unwanted swings and motions in floating wind turbines

A novel strategy to reduce unwanted swings and motions in floating wind turbines is presented. At above rated wind speeds, the platform, on which the wind turbine is mounted, causes the generator speed control loop to become unstable. The proposed strategy assures stability of the control loop by an additive adjustment of the measured generator speed using tower fictitious forces. The developed strategy is independent of the platform and wave dynamics

Gusts detection in a horizontal wind turbine by monitoring of innovations error of an extended Kalman filter

This paper presents a novel model-based detection scheme capable of detecting and diagnosing gusts. Detection is achieved by monitoring the innovations error (i.e., the difference between the estimated and measured outputs) of an extended discrete Kalman filter. It is designed to trigger a detection/confirmation alarm in the presence of wind anomalies. Simulation results are presented to demonstrate that both operating and coherent extreme wind gusts can successfully be detected. The wind anomaly is identified in magnitude and shape through maximum likelihood ratio and goodness of fit, respectively. The detector is capable of isolating extreme wind gusts before the turbine over speeds

Wind turbine control design to enhance the fault ride-through capability

This paper presents a control strategy for wind turbines to enhance their fault ride-through capability. The controller design is based on pitch controlled variable speed wind turbine equipped with doubly-fed induction generator (DFIG). The fault ride-through is realized by injecting a crowbar with variable resistance on the generator rotor circuit. To reduce the mechanical loads induced by grid faults, the wind turbine controller is improved by means of filtering techniques which alleviate the loads on the turbine blades and drive-train. The performance of the control strategy is tested by simulation. It is shown that the combined mechanical and electrical controller design significantly improves the wind turbine fault ride-through capability

Wind turbine Cpmax and drivetrain-losses estimation using Gaussian process machine learning

In this paper it is shown that measured data in a wind turbine, available to the controller, can be formulated into a polynomial regression problem in order to estimate the turbine's maximum efficiency power coefficient, Cpmax, and drivetrain losses, assuming the latter can be well approximated as being linear. Gaussian process (GP) machine learning is used for the regression problem. These formulations are tested on data generated using the Supergen Exemplar 5 MW wind turbine model, with results indicating that this is a potential low cost method for detecting changes in aerodynamic efficiency and drivetrain losses. The GP approach is benchmarked against standard least-squares (LS) regression, with the GP shown to be the superior method in this case

Detection and compensation of anomalous conditions in a wind turbine

Anomalies in the wind field and structural anomalies can cause unbalanced loads on the components and structure of a wind turbine. For example, large unbalanced rotor loads could arise from blades sweeping through low level jets resulting in wind shear, which is an example of anomaly. The lifespan of the blades could be increased if wind shear can be detected and appropriately compensated. The work presented in this paper proposes a novel anomaly detection and compensation scheme based on the Extended Kalman Filter. Simulation results are presented demonstrating that it can successfully be used to facilitate the early detection of various anomalous conditions, including wind shear, mass imbalance, aerodynamic imbalance and extreme gusts, and also that the wind turbine controllers can subsequently be modified to take appropriate diagnostic action to compensate for such anomalous conditions

Developing the next generation of renewable energy technologies: an overview of low-TRL EU-funded research projects

A cluster of eleven research and innovation projects, funded under the same call of the EU’s H2020 programme, are developing breakthrough and game-changing renewable energy technologies that will form the backbone of the energy system by 2030 and 2050 are, at present, at an early stage of development. These projects have joined forces at a collaborative workshop, entitled ‘ Low-TRL Renewable Energy Technologies’, at the 10th Sustainable Places Conference (SP2022), to share their insights, present their projects’ progress and achievements to date, and expose their approach for exploitation and market uptake of their solutions