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Analysing the Lifetime of a Wind Turbine

Holzmuller 1bOperation Beyond Design Life

According to IEC 61400 [1], the lifetime of a wind turbine is a minimum of 20 years . However, differences between the design loads and the actual loads on site can lead to the possibility of operating the wind energy converter (WEC) longer than the design life. Using an aeroelastic simulation the individual overall lifetime can be calculated for each main component.

By Jürgen Holzmüller, President, 8.2 Group, Germany

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Edgewise Vibration and Wind Turbine Blade Failure

Investigating the Causes and Mitigating the Risks

EV Figure 1Edgewise vibration (EV) is an aeroelastic resonant phenomenon induced by the wind that can occur when a wind turbine is parked with a brake applied or idling (e.g. not producing power). While EV is an infrequent event, the authors have conducted several blade failure investigations that identified EV as the mechanism of failure. The investigations involved blades designed and manufactured by multiple entities, with blade lengths ranging from approximately 40 metres to more than 80 metres. This range encompasses most utility-scale blade lengths currently in production. EV is a specific case of vortex-induced vibration, where shed vortices in fluid flow around a structure impart forces to the structure, resulting in oscillatory motion. EV is characterised by increasing blade deflections (Figure 1), primarily in the edgewise direction, that (for the context of this article) results in blade damage.

By M. Malkin, Principal Engineer, and D. Griffin, Senior Principal Engineer, DNV GL, USA

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Service Life of Blade Bearings

Problems Faced in Service Life Estimation of Blade Bearings

Schwack Figure1The blade bearings of wind turbines allow the required oscillation to control the loads and power of the wind turbine. The pitch system brings the blade to the desired position by adapting the aerodynamic angle of attack. The pitch bearing, which is connected to the blade and the hub of the turbine, is subjected to high axial forces and bending moments. The conditions of these bearings are unique and most standards to estimate bearing service life are designed for rotating bearings and do not consider the oscillation. This article gives a brief overview of the current problems of blade bearings. The article focuses on the tribological challenges like fatigue life calculation of oscillating bearings, different wear damage modes like false brinelling and fretting wear, grease lubrication and the contact conditions occurring under different operating environments.

By Fabian Schwack and Prof. Dr.-Ing. Gerhard Poll, Institute of Machine Design and Tribology, Germany

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Performance Monitoring on all Wind Turbines at any Time

Spinner Anemometer Provides Transparency in the Performance of All Turbines in a Wind Farm

Wind turbines are energy producing devices. Hence it is important for the customer and the manufacturer to know if a turbine efficiently converts the kinetic energy from the given wind conditions into power. This power performance characteristic is commonly expressed as electrical power (output) versus horizontal wind speed (input) measured under free inflow conditions at a distance of two to four rotor diameters in front of the turbine. Here is where the big dilemma in the wind industry lies.

 Romo Wind 1a Romo Wind 1b

On the one hand every turbine should be monitored to make sure its performance characteristic is within the specification, but on the other hand it is almost impossible to measure the wind quantities at all turbines and at all sites, using met masts or other non-standard forward-looking measurement systems.

By Harald Hohlen, ROMO Wind

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Surveillance of Offshore Wind Farms

DOC fig 1Security and Protection Using Sensor Systems

Sensor systems for offshore wind farms are used for the monitoring of many environmental and operational parameters. They monitor the internal turbine and loads condition, and also the environment of offshore wind farms. Wind speeds, wave heights and swell, as well as parameters related to the turbine condition such as oil temperature or pressure or rotor speed, are measured by sensor systems. However, sensors are also vital for safety and security. Each offshore wind farm element must be equipped with a fire detection system, which is based on sensor information. Access restrictions to sensitive areas (e.g. the monitoring room or nacelle) are also managed by sensors, and sensor systems guarantee the safe condition and positioning of rotor and nacelle (yaw system). The research project OWiSS, which is described below, focuses in particular on the safety and security issues.

By Julia Klatt, Deutsche Offshore Consult, Germany

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Advances in Wind Turbine Mooring

First Subsea Figure 1 Ball and TaperDevelopments in Mooring Installation Technology for Floating Offshore Wind Structures

As floating wind turbines move into deeper waters, the capital expenditure (CAPEX) costs for mooring and installation will contribute a significant proportion of the overall project budget. Offshore wind developers are looking for a new mooring methodology to reduce costs, minimise installation times and reduce health and safety risks. The mooring of offshore wind platforms has been identified as the critical success factor in the future of floating offshore wind. High installation costs and the cost of anchoring are delaying and restricting the commercialisation of the sector.

By Greg Campbell-Smith, Global Business Development Manager, First Subsea, UK

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Machine Learning Strategies for SCADA Data

Jan Helsen Figure1Faster Failure Detection in Wind Turbine Drive-Trains

Machine learning is finding its way into wind energy. It can be beneficial in many aspects of the wind industry value chain, ranging from the planning phase of new farms to operational optimisation during their service life. For the latter it has big potential. A turbine has many sensors that allow detailed monitoring of its operation and this operational data can be used as input for machine learning strategies. By tailoring maintenance strategies to the information coming from anomaly detection based on monitoring algorithms maintenance can be optimised and turbine uptime improved. In particular by using already available SCADA sensor data, optimisation potential can be realised rapidly.

By Prof. Jan Helsen and Ing. Pieter Jan Jordaens, OWI-lab, Belgium

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