Impact of wind conditions on thermal loading of PMSG wind turbine power converters

Power converter reliability is critical for permanent magnet synchronous generator (PMSG) wind turbines. Converter failures are linked to power module thermal loading but studies often neglect turbine dynamics, control and the impact of wind speed sampling rate on lifetime estimation. This paper addresses this using a 2MW direct-drive PMSG wind turbine model with a 2-level converter, and simulating junction temperatures (Tj) using a power module thermal equivalent circuit under various synthetic wind speed conditions. These synthetic wind conditions include constant and square wave profiles representing stable and gusty wind conditions. Responses to square wave wind speeds showed that the lower the gust frequency, the higher ∆Tj becomes, demonstrating that low turbulence sites have greater thermal variation in the converter. In contrast, wind speed variations with frequencies greater than 0.25Hz deliver only small increases in ∆Tj . It is concluded that reasonable approximations of Tj profiles can be made with 0.25Hz wind speed data, but that lower data rate wind measurements miss essential, damaging characteristics

Monitoring Wind Turbine Loading Using Power Converter Signals

The ability to detect faults and predict loads on a wind turbine drivetrain's mechanical components cost-effectively is critical to making the cost of wind energy competitive. In order to investigate whether this is possible using the readily available power converter current signals, an existing permanent magnet synchronous generator based wind energy conversion system computer model was modified to include a grid-side converter (GSC) for an improved converter model and a gearbox. The GSC maintains a constant DC link voltage via vector control. The gearbox was modelled as a 3-mass model to allow faults to be included. Gusts and gearbox faults were introduced to investigate the ability of the machine side converter (MSC) current (I q) to detect and quantify loads on the mechanical components. In this model, gearbox faults were not detectable in the I q signal due to shaft stiffness and damping interaction. However, a model that predicts the load change on mechanical wind turbine components using I q was developed and verified using synthetic and real wind data

Evaluation of Synthetic Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms

A method for synthesising wind speed time series (WSTS) from limited data is required that can be used for reliability examination of wind farms and maintenance strategies for a range of wind speed scenarios. Key characteristics of the wind resource need to be captured, including energy availability and maintenance weather windows. 4 WSTS simulators were used to produce synthetic WSTS based on benchmark data from a meteorological mast data at the offshore Egmond aan Zee wind farm in the Netherlands. These synthetic WSTS were compared with test criteria to determine their suitability for reliability analysis. This included comparing the synthetic WSTS to the benchmark data in terms of the energy availability in the wind and from a typical turbine, residence time at wind speeds, number of transitions between 1m/s wind speed bins, replication of seasonal characteristics including weather windows, and underlying statistical properties. Based on the chosen criteria, the most appropriate WSTS simulator was the modified Markov process. However, no modelling technique performed best against all criteria and none capture the autocorrelation function (ACF) as closely as desired. Therefore, there is scope for a more advanced technique for wind speed modelling for reliability analysis which combines the best aspects of the models used in this work

Experimental Set-up for Applying Wind Turbine Operating Profiles to the Nacelle Power Converter

Studies have shown that the reliability of fully rated converters (FRC) in permanent magnet synchronous generator (PMSG) wind turbines is critical. This paper outlines an experimental rig that applies PMSG wind turbine specific operating profiles to a machine side converter (MSC) power module. A number of test regimes have been designed to verify thermal models of the power module, validate the use of cycle life vs. Tj profile manufacturing data, and determine the wind turbine operational profiles that cause the most damage to the MSC

Modelling and Evaluation of Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms

This paper outlines proposed testing criteria for wind speed time series (WSTS) models. The objective is to assess their suitability for reliability analysis that is dependent on an accurate representation of weather patterns. Two WSTS models were analysed for their suitability against these criteria. The Markov model was found to be suitable for resource assessment, but would require modification before it could represent weather patterns, whilst the random sampling model could represent weather patterns more accurately, but could not be used for resource assessment

Wind Energy: UK Experiences and Offshore Operational Challenges

This paper presents a discussion of the development of wind energy generation in the United Kingdom and the challenges faced by the wind industry including reliability, performance and condition monitoring, particularly in the offshore environment. The worldwide installed capacity of offshore wind has now risen to over 7 GW, with an ever increasing deployment rate of new assets. About 90% of the global currently installed capacity is in Northern Europe, with the United Kingdom having the world's largest share at 4 GW. Capacity factor data from UK offshore wind farms is presented, providing an insight into the current performance of large Round 2 offshore wind farms compared to the earlier Round 1 farms and to onshore farms. The data reveal that the United Kingdom's Round 2 offshore farms are achieving an average monthly capacity factor of 38.3% with a peak value of 75.8%. The older Round 1 farms have a lower average capacity factor of 33.6% while large onshore farms with capacities above 100 MW have achieved 25.6%. Offshore wind turbine performance has improved over time, and the industry is applying the learning from early experiences to achieve better performances at the more recently installed farms. Despite these improvements in turbine availability, the cost of energy from wind, particularly offshore, remains too high for it to be a commercially viable form of generation without subsidies. Reducing the cost of energy from wind to economically sustainable levels is the most important challenge facing the industry today. Operation and maintenance costs constitute up to 30 % of the total cost of energy from wind in large farms. The industry must overcome the challenges associated with improving component reliability and the development and adoption by operators of appropriate condition monitoring systems and maintenance strategies, in order to reduce costs to sustainable levels. Research and development work carried out with these goals in mind is also reviewed in the paper

Power Converter Junction Temperature Measurement using Infra-red Sensors

Studies demonstrate that the power converter has one of the highest failure rates in a wind turbine, with a key failure driver being the power module junction temperature ( T j ). This paper details an experimental setup for simplified emulation of wind turbine conditions on a power converter with infra-red sensing of IGBT T j . Results are compared to previous simulation work for a PMSG wind turbine, with the same trend of increasing mean T j with wind speed found, and the need to use an equivalent generator reactance in highlighted. A commercial-scale prototype for more accurate wind turbine converter emulation is also detailed

Determining the Wind Speed Distribution within a Wind Farm considering Site Wind Characteristics and Wake Effects

This paper introduces a wind speed model for simulating the distribution of wind speeds within a wind farm. The model combines a macro scale wind speed time series (WSTS) model based on a continuous Markov process with a wake flow model, based on the Jensen model, to produce wind speeds upwind of every wind turbine. This model has been designed for use in the testing of turbine coordinated control algorithms and for use in detailed reliability analysis. An example analysis was carried out to investigate the Annual Energy Not Produced (AENP) due to wake effects on a single string wind farm. It was found that the wakes accounted for a 20.2% reduction in energy production compared to the wakeless scenario, highlighting the need to model these wake effects

Cost-effective condition monitoring for wind turbines

Cost-effective wind turbine (WT) condition monitoring assumes more importance as turbine sizes increase and they are placed in more remote locations, for example, offshore. Conventional condition monitoring techniques, such as vibration, lubrication oil, and generator current signal analysis, require the deployment of a variety of sensors and computationally intensive analysis techniques. This paper describes a WT condition monitoring technique that uses the generator output power and rotational speed to derive a fault detection signal. The detection algorithm uses a continuous-wavelet-transform-based adaptive filter to track the energy in the prescribed time-varying fault-related frequency bands in the power signal. The central frequency of the filter is controlled by the generator speed, and the filter bandwidth is adapted to the speed fluctuation. Using this technique, fault features can be extracted, with low calculation times, from direct- or indirect-drive fixed- or variable-speed WTs. The proposed technique has been validated experimentally on a WT drive train test rig. A synchronous or induction generator was successively installed on the test rig, and both mechanical and electrical fault like perturbations were successfully detected when applied to the test rig