Modeling the effects of seasonal weather and site conditions on wind turbine failure modes

It is important that the impact of the offshore environment on wind turbine reliability is reduced significantly due to the importance of offshore wind deployment to global energy targets. Future development may otherwise be compromised by unsustainable operation and maintenance (O&M) costs. This paper aims to improve the accuracy of offshore O&M models by accounting for any relationship between certain weather characteristics and wind turbine failure modes. This is done using maintenance data from a UK onshore wind farm and weather data from a weather station located nearby. Non-parametric Mixture Models are estimated from the data and they are used to calculate a more accurate, weather dependent, failure rate which will be used in future research for Markov Chain Monte Carlo Simulation. This research will be of particular interest to wind turbine operators and manufacturer

Quantification of over-speed risk in wind turbine fleets

The effective life management of large and diverse fleets of wind turbines is a new problem facing power system utilities. More specifically, the minimization of over-speed risk is of high importance due to the related impacts of possible loss of life and economic implications of over-speed, such as a loss of containment event. Meeting the goal of risk minimization is complicated by the large range of turbine types present in a typical fleet. These turbines may have different pitch systems, over-speed detection systems and also different levels of functional redundancy, implying different levels of risk. The purpose of this work is to carry out a quantitative comparison of over-speed risk in different turbine configurations, using a Markov process to model detection of faults and repair actions. In the medium-long term, the risk associated with different assets can used as a decision making aid. For example if the operator is a utility, it may want to avoid purchasing high risk sites in the future, or may need to develop mitigation strategies for turbines at high risk of over speed

Condition monitoring benefit for offshore wind turbines

As more offshore wind parks are commissioned, the focus will inevitably shift from a planning, construction and warranty focus to an operation, maintenance and investment payback focus. In this latter case, both short-term risks associated with wind turbine component assemblies, and longterm risks related to structural integrity of the support structure, are highly important. This research focuses on the role of condition monitoring to lower costs associated with short-term reliability and long-term asset integrity. This enables comparative estimates of life cycle costs and reduction in uncertainty, both of which are of value to investors

Techno-economic comparison of operational aspects for direct drive and gearbox-driven wind turbines

The majority of wind turbines currently in operation have the conventional Danish concept design-that is, the three-bladed rotor of such turbines is indirectly coupled with an electrical generator via a gearbox. Recent technological developments have enabled direct drive wind turbines to become economically feasible. Potentially, direct drive wind turbines may enjoy higher levels of availability due to the removal of the gearbox from the design. However, this is only a theory: so far not substantiated by detailed analytic calculation. By providing such a calculation, this paper enables us to quantitatively evaluate technical and economic merits of direct drive and gearbox-driven wind turbines

Modelling the impact of the environment on offshore wind turbine failure rates

For offshore wind turbines to become an economical energy generation option it is vital that the impact of the offshore environment on reliability is understood. This paper aims to model the impact of the wind speed and the external humidity and temperature. This is achieved using reliability data comprising of two modern, large scale wind farm sites consisting of approximately 380 wind turbine years of data. Weather data comes from a nearby weather station and an onsite met mast. A model is developed, using the reliability data, which calculates weather dependant failure rates and downtimes which are used to populate a Markov Chain. Monte Carlo simulation is then exercised to simulate the lifetime of a large scale wind farm which is subjected to controlled weather conditions. The model then calculates wind farm availability and component seasonal failure rates. Results show that offshore, the wind speed will have the biggest impact on component reliability, increasing the wind turbine failure rate by approximately 61%. The components affected most by this are the control system and the drive train. The higher offshore wind speeds appear to cause a higher proportion of major failures than experienced onshore. Research from this paper will be of interest to operators and wind turbine manufacturers who are interested in maintenance costs and logistics

Towards quantification of condition monitoring benefit for wind turbine generators

Condition monitoring systems are increasingly installed in wind turbine generators with the goal of providing component-specific information to the wind farm operator and hence increase equipment availability through maintenance and operating actions based on this information. In some cases, however, the economic benefits of such systems are unclear. A quantitative measure of these benefits may therefore be of value to utilities and O&M groups involved in planning and operating wind farm installations. The development of a probabilistic model based on discrete-time Markov Chain solved via Monte Carlo methods to meet these requirements is illustrated. Potential value is demonstrated through case study simulations

Operational strategies for offshore wind turbines to mitigate failure rate uncertainty on operational costs and revenue

Several operational strategies for offshore wind farms have been established and explored in order to improve understanding of operational costs with a focus on heavy lift vessel strategies. Additionally, an investigation into the uncertainty surrounding failure behaviour has been performed identifying the robustness of different strategies. Four operational strategies were considered: fix on fail, batch repair, annual charter and purchase. A range of failure rates have been explored identifying the key cost drivers and under which circumstances an operator would choose to adopt them. When failures are low, the fix on fail and batch strategies perform best and allow flexibility of operating strategy. When failures are high, purchase becomes optimal and is least sensitive to increasing failure rate. Late life failure distributions based on mechanical and electrical components behaviour have been explored. Increased operating costs because of wear-out failures have been quantified. An increase in minor failures principally increase lost revenue costs and can be mitigated by deploying increased maintenance resources. An increase in larger failures primarily increases vessel and repair costs. Adopting a purchase strategy can negate the vessel cost increase; however, significant cost increases are still observed. Maintenance actions requiring the use of heavy lift vessels, currently drive train components and blades are identified as critical for proactive maintenance to minimise overall maintenance costs

Analysis of offshore wind turbine operation & maintenance using a novel time domain meteo-ocean modeling approach

This paper presents a novel approach to repair modeling using a time domain Auto-Regressive model to represent meteo-ocean site conditions. The short term hourly correlations, medium term access windows of periods up to days and the annual distibution of site data are captured. In addition, seasonality is included. Correlation observed between wind and wave site can be incorporated if simultaneous data exists. Using this approach a time series for both significant wave height and mean wind speed is described. This allows MTTR to be implemented within the reliability simulation as a variable process, dependent on significant wave height. This approach automatically captures site characteristics including seasonality and allows for complex analysis using time dependent constaints such as working patterns to be implemented. A simple cost model for lost revenues determined by the concurrent simulated wind speed is also presented. A preliminary investigation of the influence of component reliability and access thresholds at various existing sites on availability is presented demonstrating the abiltiy of the modeling approach to offer new insights into offshore wind turbine operation and maintenance

Choreography of silk spinning by webspinners (Insecta: Embioptera) reflects lifestyle and hints at phylogeny

Silk spinning defines the morphologically constrained embiopterans. All individuals spin for protection, including immatures, adult males and the wingless females. Enlarged front tarsi are packed with silk glands and clothed with ejectors. They spin by stepping with their front feet and releasing silk against substrates and onto preexisting silk, often cloth-like. Spinning is stereotypical and appears to differ between species in frequency and probability of transition between two spin-step positions. This spinning choreography was assessed using thousands of spin-steps scored in the laboratory for 22 species to test: (1) the body size hypothesis predicting that spinning would be more complex for larger species; and (2) the phylogeny hypothesis which predicted that spinning would display phylogenetic signal. Tests relied on published phylogenies for the order Embioptera. Independent contrast analysis revealed relationships between five spin characteristics and body size, whereby, for example, larger webspinners invested in relatively larger prothoracic tarsi used for spinning and in spin-steps that would yield expansive silk coverings. Spin-step dynamics displayed a phylogenetic signal for the frequency of six spin-steps and for 16 spin-step transitions. Discussion focuses on patterns revealed by analysis of phylogenetic signal and the relationship to life style and to recently discovered chemical characteristics of silk