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Lifting in Confined Spaces
Lifting in a confined space can be both dangerous and difficult. Very often there is not enough room for a conventional crane or a traditional lifting device, so the employee ends up performing the heavy lifts manually. It takes time, and unfortunately it also causes a great number of personal injuries every year. This article focuses on the safety aspects of lifting in confined spaces such as inside wind turbines and illustrates how a flexible crane can make it possible to cut manual handling to a minimum.
By Jesper Friis-Wandall Nielsen, Sales Director, FlexiCrane, Denmark
A flexible crane that is easy to use and which can move loads around corners and obstacles, through narrow openings and in all directions provides wholly new possibilities and means a major difference to safety and the working environment.
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A Grease with Low Base Oil Viscosity Improves Main Bearing Lubrication
The lubrication of main bearings in wind turbines is a difficult business. The lubricant has to cope with false brinelling, with challenging operating aspects such as high loads and varying temperatures, and with the need to protect components against wear. Last, but not least, lubricants have to be useable in centralised 
lubricating systems. The classical approach in wind turbine main bearing lubrication has been to use greases with a high base oil viscosity, which were regarded as the optimum. Meanwhile, bench tests and field experience have shown that greases with a low base oil viscosity (i.e. in the range of 130–150mm/s2) can protect the bearing better than other lubricants. The key to success is the combination of the low-viscosity base oil with suitable extreme pressure and antiwear additives.
By Thomas Jørgensen, Klüber Lubrication, Germany
Increased Challenges for Wind Turbines
Wear protection under high loads and vibrations, good grease distribution, efficient oil separation and reduction of component temperatures are some of the issues which need to be considered, especially for main rotor bearings in both geared and direct-drive turbines. There are further challenges for manufacturers of lubricants from developments in turbine technology. One development has been the tendency for turbines to have higher power generation capacities, which also means that they have bigger and heavier rotor bearings. A second trend has been the requirement of longer lifetime (i.e. a minimum of 20 to 25 years). These conflicting requirements make the main bearing an extremely challenging application. Mechanical challenges which have been known from the early days of wind turbine design are becoming even more obvious with increasing turbine dimensions. The fact that the bearings operate at low speed and, at the same time, are subjected to alternating loads and torques with constantly varying directions of loads and movements, are problems that the industry is still trying to solve using a variety of techniques.
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Market Demand Drives Development of New Solutions
With the growth of the wind industry and introduction of turbines of more than 1MW, greater loads and increased stresses are affecting mainshaft and gearbox bearing life. Damage and failure modes are occurring sooner than expected, and for many wind farm operators the cost of unexpected down-tower repairs is adding up. As a result, the industry is asking for longer life from mainshaft and gearbox bearings.
By Guillaume Badard, The Timken Company, France
Current Design Challenges
Modular wind turbine designs commonly use two-row spherical roller bearings (SRBs) to support and carry the mainshaft loads. In fact, SRBs dominate the modular turbine market in two different configurations, three- and four-point mounts. These configurations are shown in Figure 1.
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How to Use the Whole Potential of Wind Farm Data
Wind farm SCADA data holds an enormous potential for plant performance improvement and should be an essential tool for operation and maintenance (O&M). The proper analysis of key variables can lead to important benefits through the improvement of turbine performance, as well as cost reductions through optimisation of the O&M strategy and extension of the lifetime of components. Because of the huge amount of information contained in SCADA, specific analysis techniques need to be designed and applied to get the most from the data. In the following article, the authors explain some of the best available methods for SCADA data analysis, the most common issues identified in operational wind farms and the benefits obtained through this kind of analysis.
By Claudia Puyals, Plant Performance Analyst, AWS Truepower, Spain
Wind farm SCADA contains a large amount of highly valuable information that in most cases is not exploited at its maximum level. In general, only a small fraction of SCADA data is analysed, even for those wind farms integrated into control centres. Furthermore, the analysis is frequently only superficial.
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A Forestry Focus
As existing wind farms are maturing, owners and operators are beginning to scrutinise operational performance, placing additional focus on performance enhancement. Considerable attention has been paid, in recent years, to reliability and maintenance optimisation, but the focus is now intensifying on making the most of existing assets and, importantly, their return on investment.
By Alan Mortimer, Director of Innovation, SgurrEnergy, UK
Technology advances and a more in-depth understanding of wind is beginning to show that, in many cases, wind farms have not been optimally designed for real on-site wind conditions and related constraining factors. The opportunity exists for wind farm owners to realise substantial commercial gain through improvements that are focused on control, aerodynamics and the local environment.
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Lessons Learnt and Future Opportunities
In August 2012 SOWITEC won the tender for Vientos de Pastorale (Pastorale), a Uruguayan wind farm in the southwest of the country (Figure 1) and was granted a 20-year power purchase agreement (PPA) at a price of US$ 63.5/MWh. On 23 February 2016 financial close was successfully reached on the debt and equity components for Pastorale. The close is the first in the country to be carried out with commercial lenders and on a non-recourse basis. It allows start of construction on time and commissioning before mid-2017. Lessons learnt in the areas of technology, standardisation of tender documentation and lending are presented below. Opportunities for the country’s wind power system are also addressed.
By Rosa Tarragó, Head of Structured Finance, SOWITEC, Germany
As indicated in the figures published by the Global Wind Energy Council (GWEC) in April 2016, Uruguay has experienced rapid development in the wind energy sector since 2010. At the end of 2015 the country’s total wind power capacity amounted to 845MW, supplying 19.5% of the country’s electricity demand.
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Detecting Faults Long Before the Damage
A key term of Industry 4.0 is ‘predictive maintenance’ – the forecast of damaging events long before they occur. The software company Indalyz Monitoring & Prognostics (IM&P) GmbH, which is based in the city of Halle (Saale) in the German Federal State of Saxony-Anhalt, has developed an innovative predictive maintenance software solution. This software is based on artificially intelligent algorithms that forecast when an individual component of a machine, complex plant or a machine cluster will reach its critical level or even break down. Future malfunctions are predicted long before the damage event occurs. The operator of a facility such as a wind park can thus organise service, material and personnel efficiently, which in turn reduces the operating costs and downtimes.
By Prof. Dr. Michael Schulz (IM&P) and Tanja Ruedinger (Investment and Marketing Corporation Saxony-Anhalt), Germany
Modern machines have a highly complex technical structure which makes them very costly and maintenance-intensive. It therefore makes economic sense to use each component up to the loss of functionality but at the same time to minimise maintenance costs and reduce downtimes to a minimum. To achieve all this, a pioneering maintenance concept is needed: predictive maintenance.
