Deliverable Reports

Abstracts for the public project deliverables and links to the full documents can be found below:

Deliverable D1.1: Collection of failure data for onshore and offshore wind farms

Abstract: Wind turbines are complex systems consisting of a variety of critical components (e.g. tower, blades, rotor hub, sensors, gearbox, power electronics, yaw, brake mechanism, controller, anemometer, etc.). Failure of any of these critical components will most likely result in unnecessary downtime and associated costs due to the loss of production and repair requirements. Depending on the type of component and mode of failure the effect on the overall downtime, repair timescale and financial losses can vary significantly. Thus, gearbox failures may result in far longer downtime and maintenance costs than failures associated with sensors. Furthermore, certain types of failures may result in significant damage to other components or even complete loss of the wind turbine. For example, an overheating bearing causing combustion of the lubricating oil will probably lead to the complete loss of all the equipment installed on the nacelle. Also failure of the braking mechanism under severe windy conditions may also result in catastrophic structural failure of the blades and possibly the wind turbine itself.

The purpose of this deliverable report is to present the data collected with the help of the industrial partners of the consortium about the failure modes that affect wind turbines. Due to confidentiality issues the distinction between onshore and offshore wind farm data is not always straightforward but the report contains sufficient detail in order to enable satisfactory conclusions to be drawn with regards to the main problems faced in wind turbine operation whether these are onshore or offshore. To the extent that it has been possible public releases have been considered to increase the amount of useful information contained in this report. According to the findings the gearbox condition is a critical factor for both onshore and offshore wind farms as it can result in significant downtime and repair costs. Although wind turbine manufacturers and operators demand that the gearbox is designed for an operational lifetime of at least 20 years this is far from being achieved. According to reports most operators are faced with gearbox refurbishment or even replacement at least twice or thrice within a 20 year period of operation. In recent wind energy projects the costs associated with gearbox problems are always taken into consideration during budgetary planning.

Link to full report: D1.1 report

 

Deliverable D1.2: Assessment of condition monitoring systems employed

Abstract: In this deliverable report the consortium has collected, analysed and evaluated the information available on existing commercial, pre-commercial and research-based condition monitoring systems with respect to their technical characteristics, efficiency, reliability, cost and easiness of installation on non-instrumented wind turbines. At the same time, the operational requirements set by wind turbine manufacturers and operators for the minimisation of occurrence of faults and failures have been assessed and are presented in this report. The efficiency and reliability of existing systems have been compared with the operational requirements as these have been set by wind turbine operators and manufacturers in order to optimise wind turbine operation. The results that have been presented in this report have been taken into account in order to ensure that a substantial step-change in the efficiency and reliability of wind turbine operation will be realised and demonstrated by the end of the OPTIMUS project.

Link to full report: D1.2 report

 

Deliverable D1.3: Analysis of collected data and definition of key reliability issues for wind turbines

Abstract: A significant amount of data has been collected from reports in the literature as well as the wind turbine operators involved in the OPTIMUS consortium. From the data collected and their correlation it has been revealed that for offshore wind turbines the gearbox remains the Achilles tendon of Operation and Maintenance (O&M). It has been revealed that offshore wind turbines suffer much higher gearbox failure rates than onshore wind turbines often resulting in complete gearbox replacements much earlier than anticipated. In some instances replacement gearboxes are required to be procured within a period of few months for offshore wind turbines whilst for onshore ones this period is normally extended to 6-7 years. Furthermore, onshore wind turbine gearboxes may not always require complete replacement but instead component replacement coupled with oil changes may suffice to extend the operation of the existing gearbox by up to a few more years before another extensive refurbishment or complete replacement is required.

From the limited information available on power converters it appears that the failure rates reported for both onshore and offshore wind turbines are similar or worse in onshore wind turbines. However, due to the small data sample the consortium questions the accuracy of these results. Higher failure rates are anticipated for offshore wind turbines, particularly due to the aggressive environment under which they operate.

Other components which have been reported to suffer high failure rates include the yaw and pitch systems. The control system of offshore wind turbines has also been highlighted as one of the components resulting in high periods of downtime. SCADA alarms related to the control system cannot normally be reset remotely and require access to the wind turbine by maintenance personnel in order to verify the alarm.

The wind turbine tower and foundation have so far been of least concern particularly for offshore wind turbines. Failures have only been reported for onshore wind turbines. Blade and rotor related failures according to the reports in hand appear to be higher in onshore wind turbines.

It should be emphasised that the available data do not contain information about the way maintenance has been carried out and how often complete replacements of certain wind turbine components such as the gearbox have been performed. This would influence of course the number of failures recorded and thus the failure rates as well. Investigation of offshore wind turbine gearbox reliability from published articles, papers and reports available in the literature has clearly shown that extensive gearbox replacement has been carried out in several wind farms much earlier than anticipated by the design lifetime. Replacement before failure has actually occurred means that the failure data collected are not truly representative. Therefore, it is extremely difficult to produce a quantitative reliability model. Instead we need to resort in a qualitative approach which takes into account all the known facts as well as the actual data available. It would be highly inappropriate not to question the data that have been published particularly for offshore wind farms without considering factual reports that seem to contradict the conclusions drawn from the analysis of the data alone.

Link to full report: D1.3 report

 

Deliverable D1.4: Development of energy costing model

Abstract: This document focuses on the energy costing model needed to calculate the whole lifecycle costs of wind turbines. The outcomes obtained by the model will be essential to evaluate the validity of the technology developed by the consortium.

The energy costing model will be linked with the overall wind turbine reliability model previously developed in task 1.3 (Analysis of collected data and definition of key reliability issues for wind turbines), and its theoretical cost saving benefit will be demonstrated during the field trials in WP3 (Condition monitoring of wind turbine electrical and power control systems) and WP5 (Cost-effective condition monitoring technology for wind turbines).

Link to full report: D1.4 report

 

Deliverable D2.2: Drive-train failure root cause analysis

Abstract: Wind energy is the most widely implemented renewable energy source in the world. Complex multi-MW wind turbines are currently being installed. Projects involving utility-scale wind turbines require an optimum level of reliability, availability, maintainability and safety (RAMS), in order to guarantee their financial viability in the forthcoming years.

In this deliverable report, the condition of industrial drive systems of wind turbines is qualitatively considered by fault tree analysis (FTA). Drive system involves components such as gearbox, shafts or bearings. The literature and expertise show us that these components present high failure rates and downtimes. The reliability of the drive system must be improve to reduce the operation and maintenance costs. The analysis developed in this work seed light on the importance of those elements of the drive system that should be considered to improve RAMS.

Link to full report: D2.2 report

 

Deliverable D4.1: Analysis of the effect of variable loads on condition monitoring measurements

Abstract: The variable loads that occur during normal wind turbine operation are a major problem for the valid analysis of condition monitoring data particularly when the gearbox is concerned. In this report the methods for analysing and removing the effects of variable loads on wind turbine condition monitoring have been discussed. Three types of condition monitoring measurements have been considered, including single Acoustic Emission (AE)/vibration data measurements without loading information, AE/vibration sensor data with loading information, and multiple channel vibration data without loading information. To deal with these different situations, three methods have been studied. For single sensor AE/vibration measurements, the Key Performance Index (KPI) methods can distinguish the differences between the normal and abnormal turbine operating conditions, with variable loading conditions taken into account. For AE/vibration sensor data with corresponding loading information, a baseline model method can be used to find the relationship between the feature of data measurement and loading conditions so as to take the loading conditions into account. Moreover, when the difference between the real measurement and baseline model output does not fall inside an a priori determined tolerance range, potentially abnormal/changed behaviours can be captured. It has been shown that, for the gearbox condition monitoring, the vibration baseline model is more sensitive than the AE baseline model to capture the abnormal/changed turbine behaviours. However, for the generator, the AE baseline model is much more sensitive than the vibration baseline model for condition monitoring. Finally, to deal with the multiple-channel measurements, transmissibility analysis is employed to reduce the loading effects on condition monitoring results. By using this approach, the differences between the normal and abnormal conditions can be revealed by evaluating the transmissibility functions determined from the multiple sensor data. Future work will be focused on the thresholds determination for both KPI and baseline model methods, as well as the definition of transmissibility based damage indicators.

Link to full report: D4.1 report

 

Deliverable D5.1: Assessment of condition monitoring requirements for onshore and offshore wind turbines

Abstract: In order to implement a cost-effective condition monitoring methodology the consortium has assessed the condition monitoring requirements for onshore and offshore wind turbines in terms of benefit achieved versus investment cost as well as part of insurance requirements. In determining this, the differences in failure modes and maintenance issues influencing onshore and offshore wind turbines have also been considered.

Wind turbine manufacturers and operators have shown strong demand for the development of accurate condition monitoring systems for the evaluation of the key wind turbine components in order to achieve substantial improvement in the efficiency of maintenance activities by reducing the need for reactive or corrective maintenance to the lowest possible level.

The consortium of this project is involved in the development and demonstration of an integrated condition monitoring system based on a modular design, which will enable the accurate and reliable diagnosis and prognosis of gearbox and power electronic faults. The OPTIMUS system combines the use of acoustic emission sensors and vibration sensors which can be integrated with oil particle sensors for the detection and prognosis of gearbox faults with current, voltage, vibration and temperature sensors for the assessment of the turbine’s power electronics. Integration of the aforementioned sensors allows the full assessment of the condition of two critical wind turbine components through the application of a single monitoring system based on a modular design which will also take into account generator currents and electric power output measurements.

Link to full report: D5.1 report

 

Deliverable D5.4: Field-based evaluation of achieved reliability

Abstract: The wind turbines instrumented in task 5.2 will be used to evaluate and demonstrate the achieved OPTIMUS prognostics methodology and data fusion techniques. The results obtained will be used to determine accurately the optimum condition monitoring methodology in order to keep related costs to a minimum whilst optimising availability of instrumented wind turbines and reducing downtime to an absolute minimum. Data from Acciona AW1500 turbines at the Vedadillo wind farm are considered within this task.

In this report, assessment methods and models based on fatigue life estimation are evaluated and demonstrated based on suggestions made in WP5.3. A variety of approaches have been considered and presented in this report. Each approach has been evaluated in terms of its own advantages and disadvantages and also the level of complexity of its implementation.

Using statistical comparison, detailed life estimation or fatigue damage is conducted to suggest the optimum maintenance strategy. Miner’s rule and Paris’ law with a crack propagation model are used to assess the risk of fatigue failure on the main shaft bearing.

Since frequency analysis methods are the most widely used condition monitoring methods, different numerical studies were carried out including Fourier transmissibility and Wavelet analyses methods.

Additional work was also carried out to develop a customised automated signal processing application which calculates around frequencies of interest based on gearbox specifications. The developed platform enables users to model and calculate three types of system which includes; (i) a simple bearing system consisting of a simple shaft with one or more bearings, (ii) a simple gear system consisting of one or more simple gear stages either parallel, planetary or a mix of both and (iii) a complex gearbox consisting of a combination of both bearing and gear stages with multiple stages of planetary and parallel gear meshing.

The work presented in this report also carried out a drivetrain reliability analysis as a first step towards defining the specification of a prognostic model applicable to the main bearing and gearbox of a wind turbine. This included amongst other models, the development of a main bearing life model, load monitoring, torque and bending moments. An additional life model of a generic 1.5 MW wind turbine was also developed. This was based on an existing gearbox design and knowledge of common design procedures.

Furthermore, this report also discusses the requirement for combined condition monitoring techniques and prognostic models to enhance diagnostic approaches and consequently reducing operational expenditure.

Link to full report: D5 4 report

 

Deliverable D6.3: Organisation of workshops

Abstract: As part of the strong commitment of the consortium to disseminate the key findings and outcomes of the OPTIMUS project to the wider scientific and industrial community, consortium members participated or organised a number of workshop-related events during the project. Participation in other workshops or organisation of additional workshops has also been planned after the end of the project. The activities in which the consortium members were involved, have been of varying intensity and targeting various types of audiences such as undergraduate and postgraduate students, academics, and professional members from the industry with technical and/or managerial background. In addition, the consortium members were proactive throughout the project in inviting colleagues from academia and industry to join an Advisory Group. This activity will continue beyond the end of the project as dissemination will continue strongly.

The Advisory Group members have been consulted individually during the course of the project.  However, a general workshop involving members of the Advisory Group will take place in early 2017. The event is organised by ORE Catapult and will be adjoined to a major industry event to maximise attendance, e.g. Scottish Renewables Annual Conference & Exhibition. During the project a number of special sessions were organised by Dr Mayorkinos Papaelias of the University of Birmingham in the form of special sessions at the CM conferences of 2014 and 2015. These events were open for participation to representatives from the consortium partners, Advisory Group Members and colleagues from the rest of the scientific community (academic and non-academic). Also, the Universities of Birmingham, Sheffield and UCLM carried out a number of seminars for undergraduate and postgraduate students. Workshops were also organised on annual basis in Daegu, Korea in collaboration with Kyungpook National University. At these events hosted by Professor Dongik Lee (KNU), Professor Zi-Qiang Lang (University of Sheffield – 2013), Dr Mayorkinos Papaelias (University of Birmingham – 2014) and Professor Fausto Pedro Garcia Marquez (Universidad de Castilla-La Mancha – 2015) presented the progress of the OPTIMUS project to a wide audience of postgraduate and academic staff members from KNU.

Apart from the workshops organised directly by the consortium and KNU, the University of Birmingham and TERNA Energy also took the opportunity of presenting some of the key findings of the OPTIMUS project to industrial events where they were invited as guest speakers. Participation to such events is expected to continue beyond the lifetime of the project. For example Dr Papaelias (UOB) is due to participate to the Wind Power Big Data and IoT, held in Berlin, Germany, 19-20th of October 2016. The event which is organised by BIS has attracted participation from industrial companies, research institutes and higher education establishments.

Link to full report: D6.3 report

 

Deliverable D8.2: Executive summary and public report

Abstract: The OPTIMUS project was a three year FP7 project funded by the European Community under Grant Agreement Number 322430.  The project ran from 2013 – 2016 and involved a total of 13 partners from 6 EU countries, including research organisations, SMEs, large industrial organisations and academia.  There were three main aims of the OPTIMUS project: a) to improve reliability within the wind power generation industry by delivering the prognostic technology necessary to evolve to predictive maintenance strategies, substantially reduce unexpected wind turbine failures and unnecessary costs and minimise downtime; b) to improve the efficiency of maintenance procedures and operational reliability of wind turbines and c) to support the implementation of the European Wind Initiative of the SET-Plan (SEII) and contribute significantly towards achieving the reliability, socioeconomic and environmental targets that have been set for the European wind energy industry by 2020.

In order to achieve these objectives, the consortium first undertook an assessment of current condition monitoring systems and gearbox designs, as well as an investigation into power converter and drivetrain failures.  An energy costing model was developed as part of work package, WP1.  In parallel, a dynamic drivetrain model was created (WP2), following analysis of each major mechanical component.  Once this was done, fatigue life models were created based on a 1.5MW drivetrain and a 750kW drivetrain.

Four different condition monitoring systems were installed on two different types of wind turbines, to monitor the power electronics and drive trains:

  • At Vedadillo Wind Farm (Spain) two different systems were employed on ACCIONA AW-1500 turbines:
    • INDRA installed both drivetrain condition monitoring (to measure vibration at different points of the drivetrain and the rotational speed of the high-speed gearbox shaft) and inverter condition monitoring (to monitor the power converter components’ electrical parameters)
    • INGETEAM installed inverter condition monitoring to monitor the power converter components’ electrical parameters)
  • At Chilikoka Wind Farm (Greece) TERNA, Feldman & UOB installed both vibration and acoustic emission systems on a Vestas V-47 turbine;
  • At Profitis Ilias Wind Farm (Greece), D2S installed vibration monitoring systems on a Vestas V-47 turbine.

The data from each of these turbines was collected and analysed.  A model was developed to estimate the loss of life of power electronics during wind turbine operation (WP3) and data collected from the instrumented turbines was used to validate the model.  Work was undertaken to look at the removal of variable load effects as part of work package, WP4.  Prognostic fault detection, methodology and data fusion tasks were carried out as part of WP5.  In addition to exploitation, dissemination and project management tasks, work was carried out to determine what can be done to update industry standards / guidelines and develop training procedures.

Valuable data and insights were gained during the project which have allowed the consortium to identify several readily exploitable results.  These results will be progressed by the relevant project partners after the end of the project and, where necessary, will be protected via the appropriate method (e.g. trade secret, copyright, trademark or patent).

The project findings and deliverables have been widely disseminated at both national and international level, through conference papers, journal publications and published books.

Several significant project results have been identified by the project’s Exploitation Manager and the relevant partners have submitted the details to the OPTIMUS Knowledge Portfolio.  Future work is planned which will fully exploit the project outcomes, mainly through follow-on demonstration projects with end-users.

Link to full report: D8.2 report