Wind turbine maintenance optimisation: principles of quantitative maintenance optimisation.

Maintenance optimisation is a crucial issue for industries that utilise physical assets due to its impact on costs, risks and performance. Current quantitative maintenance optimisation techniques include Modelling System Failures MSF (using monte-carlo simulation) and Delay-Time Maintenance Model (DTMM). The MSF investigates equipment failure patterns by using failure distribution, resource availability and spareholdings to determine optimum maintenance requirements. The DTMM approach examines equipment failure patterns by considering failure consequences, inspection costs and the period to determine optimum inspection intervals. This paper discusses the concept, relevance and applicability of the MSF and DTMM techniques to the wind energy industry. Institutional consideration as well as the benefits of practical implementation of the techniques are highlighted and discussed

Optimisation of wind turbine inspection intervals.

The choice of correct inspection intervals poses a serious challenge to industries that utilise physical assets. Too short an interval increases operational cost and waste production time while too long an interval increases the likelihood of unexpected asset failures. Failure Modes and Effect Criticality Analysis (FMECA) is a technique that permits qualitative evaluation of assets' functions to predict critical failure modes and the resultant consequences to determine appropriate maintenance tasks for the assets. The Delay-Time Maintenance Model (DTMM) is a quantitative maintenance optimisation technique that examines equipment failure patterns by taking into account failure consequences, inspection time and cost in order to determine optimum inspection interval. In this paper, a hybrid of FMECA and DTMM is used to assess the failure characteristics of a selected subsystems of a chosen wind turbine. Optimal inspection intervals for critical subsystems of the wind turbine are determined to minimise its total life-cycle cost

The selection of a suitable maintenance strategy for wind turbines.

Common maintenance strategies applied to wind turbines include 'Time-Based' which involves carrying out maintenance tasks at predetermined regular-intervals and 'Failur-Based' which entails using a wind turbine until it fails. However, the consequence of failure of critical components limits the adequacy of these strategies to support the current commercial drivers of the wind industry. Reliability-Centred Maintenance (RCM) is a technique used mostly to select appropriate maintenance strategies for physical assets. In this paper, a hybrid of an RCM approach and Asset Life-Cycle Analysis technique is applied to Horizontal-Axis Wind Turbines to identify possible failure modes, causes and the resultant effects on system operation. The failure consequences of critical compenents are evaluated and expressed in financial terms. Suitable Condition-Based Maintenance activities are identified and assessed over the life cycle of wind turbines to maximise the return on investment in wind farms

Significance of effective lubrication in mitigating system failures: a wind turbine gearbox case study.

The effectiveness of lubrication in machines mainly depends on the physical and chemical properties of lubricating oil, like quantity, level of suspended particles, effect of external load/shear forces, temperature amongst others. Periodic inspection of lubricating oil for its grade of viscosity, H2O content, fuel content, amount and nomenclature of suspended particles etc. assists maintenance personal in assessing the quality of oil and its residual life. Such assessments are also useful in determining health of the system in which the lubricating oil was used. This work discusses about industrial Wind Turbine Gearbox lubrication, its importance, applications, oil analysis method and lists constituents found in the oil. Results lead us to the conclusion that additives in the oil protect the gearbox from wear and tear during initial years of operation. Analysis also suggests that re-lubrication process should be performed every 18 months time interval to optimise the life of gearbox components. Other results and advice for lubrication are also listed

A SMART software package for maintenance optimisation of offshore wind turbines.

Offshore Wind Turbine (OWT) maintenance costs in between 20 - 35% of the lifetime power generation cost. Many techniques and tools that are being developed to curtail this cost are challenged by the stochastic climatic conditions of offshore location and the wind energy market. A generic and OWT centric software packages that can smartly adapt to the requirement of any offshore wind farm and optimise its maintenance, logistics and spares-holding while giving due consideration to offshore climate and market conditions will enable OWT operators to centralise their operation and maintenance planning and make significant cost reductions. This work aims to introduce the idea of a comprehensive tool that can meet the above objectives, and give examples of data and functions required. The package uses wind turbine condition monitoring data to anticipate component failure and proposes a time and maintenance implementation strategies that is developed as per the requirements of HSE and government regulations for working in the offshore locations and at heights. The software database contains key failure analysis data that will be an invaluable asset for future researchers, turbine manufacturers and operators, that will optimise OWT power generation cost and better understand OWT working. The work also lists some prevalent tools and techniques developed by industries and researchers for the wind industry

Maintenance optimisation for wind turbines

Wind is becoming an increasingly important source of energy for countries that ratify to reduce the emission of greenhouse gases and mitigate the effects of global warming. Investments in wind farms are affected by inter-related assets and stakeholders’ requirements. These requirements demand a well-founded Asset Management (AM) frame-work which is currently lacking in the wind industry. Drawing from processes, tools and techniques of AM in other industries, a structured model for AM in the wind industry is developed. The model divulges that maintenance is indispensable to the core business objectives of the wind industry. However, the common maintenance strategies applied to wind turbines are inadequate to support the current commercial drivers of the wind industry. Consequently, a hybrid approach to the selection of a suitable maintenance strategy is developed. The approach is used in a case study to demonstrate its practical application. Suitable Condition-Based Maintenance activities for wind turbines are determined. Maintenance optimisation is a means to determine the most cost-effective maintenance strategy. Field failure and maintenance data of wind turbines are collected and analysed using two quantitative maintenance optimisation techniques; Modelling System Failures (MSF) and Delay-Time Maintenance Model (DTMM). The MSF permits the evaluation of life-data samples and enables the design and simulation of a system’s model to determine optimum maintenance activities. Maximum Likelihood Estimation is used to estimate the shape (β) and scale (η) parameters of the Weibull distribution for critical components and subsystems of the wind turbines. Reliability Block Diagrams are designed using the estimated β and η to model the failures of the wind turbines and of a selected wind farm. The models are simulated to assess and optimise the reliability, availability and maintainability of the wind turbine and the farm. The DTMM examines equipment failure patterns by taking into account failure consequences, inspection time and cost in order to determine optimum inspection intervals. Defects rate (α) and mean delay-time (1/γ) of components and subsystems within the wind turbine are estimated. Optimal inspection intervals for critical subsystems of the wind turbine are then determined.EThOS - Electronic Theses Online ServiceRobert Gordon UniversityGBUnited Kingdo