◀ Back to projects overview P201101-012-TUD
DUWIND’s far offshore wind farm design PhD’s
Public summary WP 1
Offshore atmospheric conditions are expected to be favourable for wind energy purposes, however due to the distance and expenses involved in offshore atmospheric measurement campaigns, little is known about actual atmospheric conditions far offshore. To optimize wind turbine design and improve wind turbine performance far offshore, there is an urgent need to understand offshore atmospheric conditions. This should not only contribute to optimization of wind turbine design, but it should also result in a reduction in the uncertainty of atmospheric conditions that wind turbines experience in their lifetime. As such, improving our understanding of far offshore atmospheric conditions contributes to increasing the economic competitiveness of offshore wind energy.
In this PhD research project, theory is combined (and validated where needed) with observation data to obtain a physical description of the offshore atmosphere. Besides, based on numerical simulations with state of the art wind turbine design simulation software, the influence of the obtained atmospheric conditions on wind turbine performance is studied. In scope of the academic nature of the research, a reference wind turbine (5MW, 90m hub height and 126m rotor diameter) is used for simulations to compare results. Although the offshore atmosphere has a profound interaction with the sea surface, hydrodynamic loads are not considered explicitly to obtain fundamental knowledge on the interaction between wind conditions and wind turbine performance.
The rest of the public summary is available via the link below:
Public summary WP 2
The wake flow of a horizontal axis wind turbine is characterised by lower wind speed and higher turbulence than the free‑stream conditions. When clustered in large wind farms, wind turbines regularly operate inside the wake of one or more upstream machines. This is a major cause of energy production loss and a source of higher fatigue loads on the rotor’s blades. In order to minimise the wake effects, a smart optimisation of the wind-turbine layout is essential and reliable method for modelling the wake behaviour is fundamental. The scientific community has broadly recognised the high level of uncertainty, which still affects the state‑of‑the‑art numerical wake models and, in turn, leads to miscalculation of the wake effect. In order to develop more advanced models it is valuable to follow a back‑to‑basic approach and to investigate the physics of the transition from near‑wake flow to far‑wake flow. The near wake is characterised by the presence of organised structures as the tip‑ and root‑vortex helices, which are trailed at the two extremities of each blade. In the far wake, the influence of the blade flow is no longer visible: this is the region where most of the turbulence mixing happens and the wake undergoes a re‑energising process. Given the different physics governing the two regions, including in a single model a set of assumptions able to encompass both flow characteristics and to account for the influence of the near‑wake features on the far‑wake development is still problematic.
This research explores two aspects of the wake problem, adopting an experimental, numerical and theoretical approach. In the first place, the physics of the transition from near to far wake is explored. In particular, the main aim is to study how the near‑wake turbulent flow structures affect the re-energising process of the far wake, by understanding the relationship between the near‑wake vortex system and the resulting coherent turbulence structures in the wake. In second instance, the actuator disc approach, which is at the basis of most rotor as well as wake models, is studied for shedding more light onto its limitations and potentials. In the framework of the FLOW project, the main objective of this research are:
Objective 1: the delivery of an experimental database of wind turbine near- and far- wake development in controlled conditions (wind tunnel).
Objective 2: (modified) validation of several simulation codes for the development of the near-wake and its transition to a far-wake, for use in the design environment.
The complete public summary is available via the link below.
Public summary WP 3
Wind turbines that are clustered in a wind plant, have interaction with each other through the aerodynamics of the wind field in the wind plant. The aerodynamic interaction effects are caused by the turbine wakes, which are the flow structures that form behind each turbine. The wake is characterized by a reduced flow velocity caused by the extraction of energy from the flow by the turbine, and an increased turbulence intensity caused by the obstruction of the flow by the turbine. The velocity deficits will cause a decrease of electrical power production of turbines standing in the path of a wake of another turbine, and the increased turbulence may increase the fatigue loads on those downstream turbines. Wind plant control that takes into account wake interaction effects in the coordination of the control actions of the wind turbines, can enhance the performance of the wind plant, in terms of total electrical energy production, and the loads on the individual wind turbines. Enhancing wind plant performance in this way, will contribute to the reduction of the cost of offshore and onshore wind energy.
In this thesis two research objectives have been addressed: one is the evaluation of the potential of the different control degrees-of-freedom of the wind turbine to affect the interaction effect between the turbines, and the other is the development of data-driven algorithms for the optimization of those control settings in order to improve wind plant performance.
Read more about this project in the public summary via the link below.
Public summary WP 4
The current offshore maintenance organization is still facing a significant amount of unplanned and corrective actions. It is clear that this should be shifted towards more pro‐active preventive maintenance activities in the near future. In other words try to repair before a real failure occurs. The main objective of the project was to develop methods that will help to reduce corrective maintenance events. This leads to an increased availability of future far offshore wind turbines and wind farms. The project has investigated different approaches of data acquisition and monitoring as well as reliability practices. Also the use of the SCADA systems for determining abnormal conditions has been investigated.
A systematic approach for developing a more pro‐active maintenance work plan starts with an inventory of current experiences. For such purpose it is necessary to acquire a variety of operational information at different offshore locations. Data and further information was obtained from several offshore wind farms in Belgium, Denmark, the UK and The Netherlands. This information was used to analyse existing downtime events. This did not only mean that each event had to be identified, but also that the reason for each downtime had to be investigated. Ideally this identification provides the “root cause” of a downtime. This means for example that identifying an overheated gearbox as “the cause” of downtime does not suffice, it should be narrowed down to root causes such as shortage of gearbox oil due to oil pump malfunctioning, wear in a bearing or extensive wear of one of the gearwheels, just to name a few.
The complete summary can be found via the link below:
Public summary WP 5
This research addresses two challenges of making affordable electricity from offshore wind energy. The first challenge is the difficulty of optimisation, due to the multidisciplinary and multi-component nature of offshore wind farms. The second challenge is that the design of the rotor-nacelle assemblies is not performed at the same time as the design of the wind farms in which they are applied. This is the consequence of designing rotor-nacelle assemblies for many wind farms, while most of the rest of the design of the wind farm is site specific. The asynchrony between the design processes makes it difficult to optimise the rotor-nacelle assembly with respect to the cost of energy. The objective of this research is to obtain a method to support the optimisation of rotor-nacelle assemblies that will be applied in offshore wind farms.
The complete summary can be found via the link below:
Presentations
Topic 1
Windkracht 14: Meteorology, far offshore wind conditions for wind energy purposes
Topic 2
Topic 3
Windkracht 14: Controlling the wakes
Links
Topic 1
Topic 2
Experimental and numerical analysis of horizontal axis wind turbine wakes - tip vortex evolution
Experimental analysis of the wake of a horizontal-axis wind-turbine model (deliverable 6)
Topic 3
Draft Thesis: Data-driven wind plant control
The SOWFA Super-Controller: A High-Fidelity Tool for Evaluating Wind Plant Control Approaches
A Data-Driven Model for Wind Plant Power Optimization by Yaw Control
Evaluating Wake Models for Wind Farm Control
A Control-Oriented Dynamic Model for Wakes in Wind Plants
Topic 5
Partners involved
- ECN
- Eneco
- Essent
- TU Delft
Contact details
Mr. Ruud van Rooij
Project documents
Topic 1
WP1 A Holtslag, Atmosferic Stability
WP1 C Holtslag, Motheoryoffshore
WP1 D Accepted Manuscript Mcholtslag V5
Topic 2
WP2 P2 Kinetic energy entrainment
WP2 P3 Comparison piv measurements
WP2 P4 Experimental quantification
WP2 P5 Experimental analysis of the kinetic energy
WP2 P7 Exp comparison of a wt and an ad wake
WP2 P9 Potential eow solutions
WP2 P10 Validation of les and vormodel
WP2 P11 Windturbine and actuator disc wake
WP2 P12 Turb prod kin trans wake
Topic 3
WP3 Ref5 Maximum Power Point Tracking Control
WP3 Ref6 Ipv Identification Of Windturbine Rotor Vibrational Dynamics
WP3 Ref8 The Sowfa Super Controller
WP3 Ref9 Evaluating Techniques For Redirecting
WP3 Ref10 Simulation Comparison Wake Mitigation Control
WP3 Ref13 Windplant Power Optimization Through Yaw Control
WP3 Ref14 Using Particle Filters
WP3 Ref15 Evaluating Wake Models
WP3 Ref16A Control Oriented Dynamic Model
WP3 Ref17 Confidential Analysis Axial Ind Based
WP3 Ref18 Confidential Windplant System Eng
WP3 Ref19 Comparison Of Actuation Methods
WP3 Ref20 Windturbine Wake Estimation
Topic 4
p>Topic 5
WP5 P2 Dissertation MB Zaaijer
Topic 1
Estimating atmospheric stability
Validation of surface layer similarity theory
Topic 2
Topic 3
Maximum power-point tracking control for wind farms
LPV Identification of Wind Turbine Rotor Vibrational Dynamics
Evaluating techniques for redirecting turbine wakes using SOWFA
Simulation comparison of wake mitigation control strategies for a two-turbine case
Wind plant power optimization through yaw control
Wind plant power optimization through yaw control
Analysis of axial-induction-based wind plant control
Wind plant system engineering through optimization of layout and yaw control
Comparison of actuation methods for wake control in wind plants
Wind turbine wake estimation and control using FLORIDyn
Presentations
Topic 1
Far shore wind climate modelling
Topic 4
Availability based design optimisation offshore wind farms
Predicting major interventions in PAWP
Topic 5