Poster presentations

The application of big data and advanced statistical techniques

001 How Big data analytics and prognostics are improving Condition Monitoring Diagnostics Jorge Alarcon
002 Cloud-based Platform for Wind Turbine’s Health Estimation and Failure Prediction Juan-Jose Cardenas-Araujo
Researcher and Data Scientist
007 Diagnostic tools to support decision making in wind turbine operation Francisco Otal
Strategic Account Manager & OEM FES Manager
008 SCADA data analysis techniques for undeperformance diagnosis and component failure prognosis Claudia Puyals
Plant Performance Analyst
AWS Truepower
009 Baseline generation for the health assessment of a Vestas V90-3MW Wind Turbine using a vibration-based Condition Monitoring System Antonio Romero Camacho
Full Time PhD Student
010 Towards a composite health index, representative of the whole wind farm operation Mark Spring
Senior Wind Turbine Specialist
Lloyd’s Register EMEA

Predicting and enhancing turbine performance

012 Validation of the numerical model of a Horizontal Axis Wind Turbine with experimental data using two CFD codes Andrea Dal Monte
Ph.D. student
Università di Padova
014 A fuzzy logic approach for assessing turbine power performance Selena Farris
Senior Technical Manager – Methods & Innovation
The Natural Power Consultants
015 SCADA and Predictive Analytics data-based methods for Health Monitoring of Wind Turbines Jorge Acedo
Manager, Energy, R&D Control Systems Department
016 Study of the technical and financial feasibility of a predictive monitoring system for wind turbines Adão Muniz
Chesf – Companhia Hidrelétrica de São Francisco
017 Improving Turbine Performance: Yaw Misalignment and Power Curve Analysis Henrik Sundgaard Pedersen
Head of Analysis and Reporting

Post-construction yield analysis

018 The energy performance analysis of an 850 kW rated wind turbine in a peri-urban location in Ireland based on 10 years of operational data Raymond Byrne
Dundalk Institute of Technology
020 The science of seasonal forecasting for wind energy portfolios Mark Stoelinga
Senior Scientist
021 Methods for assessing losses and long term adjusting operational data in a post-construction yield analysis Johan Hansson
Kjeller Vindteknikk

Asset reporting: availability and other key metrics

023 Optimising Facility Power Curve (FPC) Calculations in South Africa Alex Olczak
Project Engineer
Wind Prospect
024 Wind Farm Performance & Availability: review of a 400MW portfolio Baris Adilogu
Senior Consultant
029 ‘Pre-Post’ ; How much they are apart?
Bob Smith
EVP – Head of International Business and Investor Relations
Mytrah Energy (India) Ltd.
030 Consistency verification and case studies of an asset performance measurement tool
Leo Hume-Wright
Wind Energy Specialist
Met Office
032 How to improve the energy ramp-up curve with performance assessment results? Itamar Lessa
Plant Peformance Leader
Casa dos Ventos
033 A Comparison of Production-based Availability Methods Francesco Vanni
Senior Engineer

Repowering, extending life or decommissioning?

036 Wind Farm Repowering: A Strategic Management Perspective Marko Bezbradica

Uppsala University
037 New approach for the Condition Monitoring System within Life Extension Strategies Antonio Fernandez
International R&D projects coordinator
Ingeteam Service S.A.
038 Achieving superior performance and extended asset life-cycle on aging wind assets though re-blading Carlo Durante
Board Member
eTa Blades
039 Can monitoring systems save your money? And if yes, what about the return of investment? Heinrich Dyck
Technical Solution Consultant
Phoenix Contact Electronics
040 Life Time Extension (LTE): how to make a reliable estimation about the real accumulated fatigue of the older turbines? Mercedes Irujo Espinosa de los Monteros
WTG life extension expert
Acciona Energia
041 Introducing a multi criteria analysis for wind farm site repowering. A case study on Gotland Hans Kerkvliet
Consultant Wind Energy
Bosch & Van Rijn
042 Determining the remaining useful life of offshore wind farms Nymfa Noppe
PhD Student
Vrije Universiteit Brussel
044 Extending the life of wind farm projects to 40+ years Alex Olczak
Project Engineer
Wind Prospect

Innovative techniques for enhanced performance

046 EDF case study: Step by step turbine performance verification and optimisation with a 4-beam nacelle-mounted Lidar Paul Mazoyer
Application engineer
048 Performance Index; A quick and efficient way to identify the odd ones.
Bob Smith
EVP – Head of International Business and Investor Relations
Mytrah Energy (India) Ltd.
049 Hybrid methodology for Wind Farm Performance Analysis: The complementarity of observation and modelling data Laurent Rakoto
Project Engineer
Maintenance Partners
050 Turbine performance evaluation with ground-based and turbine-mounted lidar Matt Smith
ZephIR Sales Manager
ZephIR Lidar
051 Characterization of wind turbine noise applied to predictive maintenance Adão Muniz
CHESF – Companhia Hidrelétrica de São Francisco

Offshore operations: lowering the costs

053 Using Offshore Remote Environmental Monitoring to Lower Operating Costs François Berry
Account Manager
AXYS Technologies

Lowering the costs of important correctives measures

056 Crane less large correctives to reduce by 25% turbines’ maintenance costs Israel Alonso Bravo
Wind Turbines Technical Trainer Specialist


Topic 1: The application of big data and advanced statistical techniques

PO.001 – How Big data analytics and prognostics are improving Condition Monitoring Diagnostics

Presenting author: Jorge Alarcon, npi, IK4-TEKNIKER

Co-author(s): Jesus Terradillos

For the last 40 years diagnostic of monitored equipment was done by experts on many different fields. Within the last years we have seen a lot of changes in the Condition monitoring field, from cheap and small sensors to very powerful software to improve the diagnostics.

But big data and prognostics are changing even more the game. Real case studies and results will be shown during the presentation.

PO.002 – Cloud-based Platform for Wind Turbine’s Health Estimation and Failure Prediction

Presenting author: Juan-Jose Cardenas-Araujo, Researcher and Data Scientist, SmartIve

Co-author(s): Alejandro Blanco-Martinez, Isaac Justicia, Jordi Cusido, Pere Marti-Puig, Jordi Solé-Casals

In this paper, we present the results obtained when using the Cloud-based Platform SmartIve to process and build prediction-engines for early diagnosis (called prognosis) in a wide set of wind turbines, with different models, makers and sizes of datasets. Specifically, we have tested the platform using SCADA-data from VESTAS, ALSTOM, GE, Fuhländer, Bonus, Gamesa and MADE wind turbines with datasets of periods ranging from six months to four years. Data comes in 5 or 10 minutes format for analogous variables and as a record of events for digital data (alarms) from the wind-park’s SCADA. The platform uses these datasets to inference prognosis models and then uses them for estimation of the health of the wind turbine and the probability of the failure for the next seven to twenty days. The platform first applies a hypothesis-testing algorithm to evaluate the viability of prediction or prognosis from 5 to 21 days ahead. Secondly, it applies a set the information-gain-based algorithms that select the near-optimal set of inputs to be considered for the model. Finally, it uses these selected variables to train a bank of classifiers-predictors ranging from partition linear models to most sophisticated and complex models as support vector machine, neural networks and Boosting-based algorithms. The obtained results have demonstrated the efficacy of the platform for prognosis on faults related with Yaw, Pitch, Main Bearing, Gear Box and Generator with accuracies ranging from 80% in the worst of the cases to 95% in the best of the cases.

PO.007 – Diagnostic tools to support decision making in wind turbine operation

Presenting author: Francisco Otal, Strategic Account Manager & OEM FES Manager, ABB

Co-author(s): Andrian Timbus

With more and more wind turbines coming online and an ever-increasing number of data points to be monitored and analyzed for each turbine, there is no doubt that big data and fleet wide analytics become more relevant for operators and service organizations managing large portfolios of such assets.

Understanding the condition of an asset can be realized in many ways, from dedicated condition monitoring equipment for each turbine component, to estimation of condition based on advanced modeling techniques, to statistical analytics over the lifetime of the asset. Each of these solutions has benefits and challenges that must be considered to determine the most effective implementation for each application.

This paper gives an overview of potential condition monitoring solutions for the wind power industry and describes in detail the implementation of fleet wide analytics using statistical tools. Specifically focusing on statistical methods that provide insight into the condition of wind turbines and predict potential failures of certain components in the future.

PO.008 – SCADA data analysis techniques for undeperformance diagnosis and component failure prognosis

Presenting author: Claudia Puyals, Plant Performance Analyst, AWS Truepower

Co-author(s): José Vidal, Jesica Piñón

Wind farm SCADA data holds an enormous potential in plant performance improvement and can definitely 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 costs reductions by optimization of O&M strategy.

A simple, preliminary assessment of plant performance and plant health can be obtained through the event or alarm log. The analysis of relevant variables as downtime, frequency of alarms per component and turbine, duration of O&M interventions, time between alarm activation and intervention, among others, allows an experienced analyst to identify major problems of the wind farm and evaluate how O&M is performed.

Almost any underperformance issue can be detected with the actual power curve of each turbine. The analysis is performed through comparison of the behavior of all the turbines in the wind farm with same characteristics and similar resource and siting conditions. However, when the wind farm has a large number of turbines, the individual comparison would be a time consuming process. In order to overcome this problem, an outlier detection algorithm can be used, which quickly identifies those power curves that differ from the rest. For an experienced analyst, the pattern of the outlier power curve provides clues about the root cause of the underperformance issue, and allows him to specify the corrective action needed to solve it.

The analysis of other variables contained in SCADA database, as for example, component temperatures, yaw and pitch angles, rotor rpm, etc., allows the prognosis of future failures in a premature stage.

In our presentation we will show examples of real world wind farms with different problems, the strategy to detect those issues, and how they look like in the SCADA data.

PO.009 – Baseline generation for the health assessment of a Vestas V90-3MW Wind Turbine using a vibration-based Condition Monitoring System

Presenting author: Antonio Romero Camacho, Full Time PhD Student, TWI Ltd

Co-author(s): Yoann Lage, Slim Soua, Tat-Hean Gan

An advanced condition monitoring system (CMS) has been developed as part of the CMSWind FP7 Project, partly funded by the European Commission (Grant Agreement no. 286854), for the assessment of wind turbine rotating parts. The validation of the system is presented in this paper. It was carried out during field trials at Bandirma Wind Energy Power Plant on a Vestas V90-3MW Wind Turbine.

This integrated CMS, which utilizes three techniques specifically designed for wind turbines and their components, will improve wind turbine machinery reliability. This estimation is made from the fact that unnecessary maintenance and out of service wind turbines are reduced or even eliminated, improving reliability and operation. Motor Current Signature Analysis (MCSA), Vibration Analysis (VA) and Acoustic Emission (AE) techniques have been used for the development of a baseline that indicates the behaviour under normal operation of three different components: the generator, the drive train (including the gearbox) and high speed shaft respectively. The work described in this manuscript will focus on the definition of the accelerometers signature as a function of the state of the healthy drive train; i.e. as a function of all the normal operating conditions or baseline. If such a consistent signature can be found then there is promise that deviations from it can be used to make advance predictions on the initiation and growth of defects that could lead to failure. These results form a satisfactory prerequisite for the identification of deviations in the sensor acquisition versus turbine power from the normal (healthy) signature, which increases the probability of detection (POD) for the CM system and its capability to detect defect growth in the drive train that could lead to impending failure.

PO.010 – Towards a composite health index, representative of the whole wind farm operation

Presenting author: Mark Spring, Senior Wind Turbine Specialist, Lloyd’s Register EMEA

Co-author(s): Marco Sepúlveda, Peter Davies

Maintenance visits to offshore wind farms are still dominated by manual resets, on-site diagnostics & reactive maintenance. Significant reductions in operating costs may be achieved by implementing established techniques of risk-based preventative maintenance. By deriving new, composite health indices, the prognostic horizon can be extended not only for high-value components such as a frequency converter, gearbox or low speed shaft bearing but also for frequent nuisance maintenance tasks on lower-value components. Significant value may be added to comprehensive & expensive condition-monitoring systems & structural health monitoring sensors by deducing the health of un-monitored components from SCADA data. LR has undertaken a comprehensive wind turbine FMEA & put together a risk-prioritised run-down of failure modes and affected systems. Using proven Axxim software, wind farm operators can set more intelligent & balanced priorities, based on failure probability and business consequences.

Topic 2: Predicting and enhancing turbine performance

PO.012 – Validation of the numerical model of a Horizontal Axis Wind Turbine with experimental data using two CFD codes

Presenting author: Andrea Dal Monte, Ph.D. student, Università di Padova

Co-author(s): Benini Ernesto

The aim of the work is the assessment of the numerical model of a Horizontal Axis Wind Turbine using the open source CFD code OpenFOAM. The obtained results are compared with both experimental and numerical data coming out from the fluid-dynamic analysis performed using the common commercial CFD Package Ansys Fluent.

The numerical model of the AOC15/50 wind turbine has been reproduced using the geometrical information of a report by SANDIA National Laboratories and validated through the experimental data provided by the National Renewable Energy Laboratory. The three blades turbine has a 15 m rotor diameter, 25 m hub height and a rotational speed of 65 rpm.

The flow domain was discretized with an unstructured tetrahedral mesh originated from the prismatic boundary layer around the blade surface.

A full three dimensional computational fluid dynamics method based on RANS approach was used, and, thanks to the symmetry of the model, only a single blade was modeled in a fraction of the cylindrical domain (120°), using periodic boundary conditions. The common boundary conditions of velocity inlet and pressure outlet were settled and the Moving Reference Frame approach was chosen.

The study replicated the experiment for wind speed velocity from 0 m/s to 24 m/s in order to reproduce the power curve of the wind turbine. Both the plots of the pressure and velocity field were provided as results.

The software comparison reveals a good agreement for both analyses in relation to the experimental data provided by the National Renewable Energy Laboratory test campaign. The results are illustrated in terms of the power curve and the power coefficients at different wind speeds. Furthermore, the velocity and pressure distributions in different sections of the flowfield are reported, along with an evaluation of the turbine power as affected by the effect of different wind speeds.

PO.014 – A fuzzy logic approach for assessing turbine power performance

Presenting author: Selena Farris, Senior Technical Manager – Methods & Innovation, The Natural Power Consultants


The first challenge in enhancing turbine power performance across a portfolio is to accurately and efficiently assess operational power performance. Real world issues including the accuracy and consistency of SCADA data, modelling uncertainty and the costs associated with monitoring campaigns complicate the assessment of turbine power performance at the portfolio level. An analytical technique using a fuzzy logic approach combining performance indicators based on operational SCADA data and pre-construction modelling is presented. This technique allows analysts to shift through the layers of uncertainty to identify the turbines that present the best opportunities for power performance improvement. After initial desktop analysis has highlighted turbines to focus on, a suite of follow-up tools including inspections and turbine-mounted lidar measurement campaigns are presented to use in a deeper investigation to confirm performance issues, rectify issues and ultimately validate performance improvements. Multiple case studies are drawn from Natural Power’s extensive experience with operating assets to demonstrate the value added through this approach to analysing turbine performance.

PO.015 – SCADA and Predictive Analytics data-based methods for Health Monitoring of Wind Turbines

Presenting author: Susana Ferreiro, I+D Researcher, IK4-TEKNIKER

Co-author(s): Jorge Acedo: [email protected]

Aitor Arnaiz: [email protected]

In recent decades, the need for renewable energy has increased the number of wind farms installed over the world. The operators of these wind farms perform the control of the wind turbines through the use of SCADA systems for data acquisition and monitoring. However, today a number of availability problems related to the corrective maintenance strategies commonly used are being encountered. The information from the SCADA is not always enough to determine the health status of the components which make up the wind turbine, which results in unexpected breakdowns and unscheduled maintenance action. These actions usually entail corrective procedures, where delivery and repair times are high and cause the wind turbine to be inoperable for long periods of time.

This paper describes the development of predictive algorithms, based on different data mining and statistical techniques, for early detection of failures in the main components of a wind turbine. Early detection of failures makes it possible to perform an assessment of the state of the wind turbine, assisting the operations staff with recommendations to avoid unexpected events, and preventing incipient failures from escalating into critical situations. The developed predictive algorithms can be integrated in second level SCADAs of wind farm owners and operators, taking into account the non-uniformity that may exist between elements of the same farm.

PO.016 – Study of the technical and financial feasibility of a predictive monitoring system for wind turbines

Presenting author: Adão Muniz, Engineer, Chesf – Companhia Hidrelétrica de São Francisco

Co-author(s): Samuel Araújo Lima; Marlos Diógenes Lucas; Paulo Henrique Pereira Silva.

Most wind turbines have the Supervisory Control and Data Acquisition (SCADA) and Condition Monitoring System (CMS) to observe its main components. Through the data provided by these systems, is possible to monitor the operation of wind turbines, and avoiding imminent or serious failures that might occur, thus enabling error correction in a short time. The SCADA is usually not configured for signs of future failure, that when corrected in time, can prevent further damages. The CMS in turn, has features that enables detection of more subtle signs compared to the SCADA, but not always the wind turbine manufacturer provides the CMS for the operator of the wind farm, which often uses products of other companies to carry out this monitoring prevention of failures.

PO.017 – Improving Turbine Performance: Yaw Misalignment and Power Curve Analysis

Presenting author: Henrik Sundgaard Pedersen, Head of Analysis and Reporting, ROMO Wind

Co-author(s): Eduardo Gil Marín, Senior data Analyst, ROMO Wind.

Introduction: Yaw misalignment is causing a significant loss of production; we have conducted measurements on more than 300 different wind turbines and more than 50% showed significant static (average) yaw misalignment.

We will present key statistics on the severity of their inability to yaw straight into the wind, how different wind turbine compare and are controlled in terms of yawing. In addition, we will illustrate through power measurement combined with our Spinner Anemometer ‘iSpin’, how yaw misalignment is causing the turbine to underperform.

Results: The Spinner Anemometer consists of three ultrasonic sensors, mounted at the spinner of a wind turbine measuring wind speed, yaw misalignment, inclination angle and from 10Hz measurements turbulence hitting the turbine.

We will compare different wind turbines from our database, to show how different designs handle dynamic yaw misalignment, and how some of the poorer performing turbines could get a significant energy boost by actively yawing more like the majority of wind turbines.

Through active power measurement combined with iSpin, we will present power curve heat maps, showing the effect of yaw misalignment on a wind turbine’s measured power curve. Additionally we will show detailed studies of average power produced, in 10min wind speed bins, as a function of degrees of yaw misalignment compared with the theoretical losses according to the Cosine Cubed and Cosine Squared rules.

Conclusion: Correcting yaw misalignment increases the wind turbine’s energy yield, according to Cosine Cube theory below rated power, though its annual energy production “AEP” more closely approximates to Cosine Squared.

The majority of wind turbines have a good yaw control system with little benefit to be gained from further optimization, but a few could increase their AEP by up to 2% if they improved their yaw strategy

Topic 3: Post-construction yield analysis

PO.018 – The energy performance analysis of an 850 kW rated wind turbine in a peri-urban location in Ireland based on 10 years of operational data

Presenting author: Raymond Byrne, Researcher, Dundalk Institute of Technology


An 850kW Vestas V52 wind turbine with a hub height of 60m and rotor diameter of 52m has been operating as an autoproducer at Dundalk Institute of Technology on the east coast of Ireland since October 2005. The turbine is located in a peri-urban area of low elevation, in the vicinity of buildings. The turbine is connected behind the campus utility meter and primarily offsets electricity imports from the utility grid. On occasion electricity is exported to the grid when the turbine power output exceeds the campus power demand. The wind turbine SCADA system measures and logs a range of internal system operational and external wind and environmental parameters in 10-minute average values. This data has been captured since the turbine started operation in 2005 and is analysed to assess the power curve and energy production performance of the turbine. Insights into the external factors, such as buildings, regional terrain, seasonal and inter-annual wind variations that have influenced the actual performance of the turbine in different wind directions are given.

PO.020 – The science of seasonal forecasting for wind energy portfolios

Presenting author: Mark Stoelinga, Senior Scientist, Vaisala


Wind energy owner/operators are subject to seasonal and interranual deviations from the wind climate, such as the significant low wind energy anomaly that occurred across much of the US during Q1 2015. These deviations can have large regional spatial coherence that can affect a wind energy portfolio, whether it consists of a few projects in a small cluster or a large geographically diverse set of projects across a continent. It is helpful to understand the scientific underpinnings of such fluctuations, and the science behind trying to predict them. Clearly the consulting industry is far from a perfect seasonal wind energy prediction capability, but advances are being made. This talk will review the science of climate variability, climate indices, climate prediction models, and statistical climate prediction techniques that are starting to clarify the forward view of seasonal portfolio performance.

PO.021 – Methods for assessing losses and long term adjusting operational data in a post-construction yield analysis

Presenting author: Johan Hansson, Advisor/Consultant, Kjeller Vindteknikk

Co-author(s): Johannes Lindvall

The ProdOptimize project, partly financed by the Swedish Energy Agency, has been running since the summer 2014 and ends in spring 2016. The project consists of three work packages (WP) that deal with different aspects of post-construction AEP assessments. WP1 has a focus on the development of methods for long term adjusting operational data and methods for estimations of potential energy production. In WP2 investigations of how a nacelle mounted lidar, a Wind Iris, can be used to optimize the production in a wind farm is made. WP3 has been focusing on the quantification of losses due to icing.

Several methods for calculating the potential energy production and long term adjusting production data from operational wind farms have been developed in the WP1 part of the project. The suitability of the different methods depends on the characteristics of the operational data, the climatic conditions at the site and the size of the wind farm.

Results from the ProdOptimize project, focusing on WP1 will be presented.

Topic 4: Asset reporting: availability and other key metrics

PO.023 – Optimising Facility Power Curve (FPC) Calculations in South Africa

Presenting author: Alex Olczak, Project Engineer, Wind Prospect

Co-author(s): David Pullinger and Matthew Behrens

As part of the Power Purchase Agreement (PPA) for projects submitted under the Renewable Energy Independent Power Producers Procurement Programme (REIPPPP) in South Africa, operators of wind farms must, at the end of the first year of operation, report a Facility Power Curve (FPC) for the asset. This power curve is used in order to calculate Deemed Energy Payments from the network operator during periods of grid downtime. A set of rules have been outlined within the PPA for each project however these are not rigidly defined and there is scope for large deviations in the FPC produced. This variation can lead to un-representative FPCs and therefore the compensation mechanism has the potential to fail to capture accurately the impact of availability on this key metric of wind farm performance.

Based on Wind Prospect’s experience as Independent Engineer on operational projects in South Africa a new methodology is presented. This method avoids many of the potential pitfalls of the PPA requirements whilst ensuring compliance with the rules and also remaining true to the intention of the metric. We also address the often limited data available for an FPC after only one year of operation – for example how to treat wind speed and direction bins with minimal data coverage.

The benefit of the proposed new approach is that a true representation of the asset’s energy production can be obtained without biases introduced due to poor turbine availability. The new method requires detailed understanding and more intensive data analysis; however it is considered that this yields benefit for both parties (buyer and seller of energy) as more accurate Deemed Energy Payments will result.

PO.024 – Wind Farm Performance & Availability: review of a 400MW portfolio

Presenting author: Baris Adiloglu, Senior Consultant, 3E

Co-author(s): Régis Decoret, Delphine de Tavernier

3E reviewed the performance of 60 wind farms, representing 450MW of turbines covering different types, technologies and generations, in Belgium, the Netherlands and France. The aim of such investigation is to assess the real technical losses (wind turbine and grid unavailability, curtailment and shadow flicker, …) in terms of downtime, but also lost production, with the view of benchmarking loss figures usually taken into account for pre-construction long term yield assessment (P50/P90). The second goal was to present updated statistics over wind turbine technical availability, since previous similar studies are already few years old (2008-2010). Results are presented as time and energy-based values this time, instead of the traditional time-based approach only.

The study is based on 10min SCADA data and wind turbine error logs directly collected from the SCADA systems, which represents a certain complexity in terms of data format and interpretation. It proposes a process to clearly identify and categorize wind turbine status for every 10min time stamp as well as various techniques to assess lost production due to wind turbine shutdown or curtailment, even when no SCADA data are actually available or reliable. At last, the study assesses the uncertainties linked to every step of the process and proposed ways forward to improve the results.

This study was initiated in October 2015 by 3E and will continue up to September 2016, or later, as more and more SCADA datasets are made available for analysis. It is expected that the final study will include approximately 100 wind farms and 700MW. However, the results are promising and already allows to quantify the actual real life losses, the wind turbine ramping up effect over availability and the impact of wind farm size over availability.

PO.029 – ‘Pre-Post’ ; How much they are apart?

Presenting author: Bob Smith, EVP – Head of International Business and Investor Relations, Mytrah Energy (India) Ltd

Co-author(s): Harry Justin (Mytrah Energy (India) Ltd), Kiran Nair (Mytrah Energy (India) Ltd), Prasad Gaitonde (Mytrah Energy (India) Ltd)

Key number for any wind portfolio financier for his model is expected energy yield. In the modern days, industry tend to have pre-construction energy assessments based on certain conservative/aggressive assumptions (especially loss assumptions and uncertainties) for a safe bet (?). This study aims to bridge the gap between pre-constructional energy estimates/loss assumptions and actual generation/real losses for operational plants (at site specific level) and thus enable the owner/banker to have a better financial planning/refinancing options for the remaining life of the project.

An investigation is performed across 14 wind farms composed of 4 different turbine manufactures and 7 different turbine models aged 2-6 years (aged less than one year is not considered to avoid stabilization issues), spread across distinct geographical regions (OEM provided).

10/14 wind farms had a better grid availability than the pre-constructional assumption. Grid augmentation of upstream network connected to the wind farms and the higher grid availability of the region (that couldn’t be envisaged during pre-constructional estimate) could have been lead to the better availability.9/14 wind farms had a better machine availability and this trend was more obvious in modern turbines. Of the 7 different turbine models, 5 of them achieved more than 98% of the guaranteed performance while one of them achieved 97%(test of one model cannot be completed due to site complexity).Hence power curve performance is validated against actual site conditions in most of the cases and higher losses/uncertainties considered in the pre-construction estimate can be reduced/removed.

Investigation results shows that there is a gap between preconstruction loss assumptions from than that of real operational conditions (both upwards and downwards) in most of the cases and a site specific post construction energy assessment incorporating the real factors can provide a better energy estimate for the rest of the life.

PO.030 – Consistency verification and case studies of an asset performance measurement tool

Presenting author: Leo Hume-Wright, Wind Energy Specialist, Met Office

To assess its suitability for use as an independent reference dataset in asset performance monitoring, low wind speed insurance, and post construction yield analyses, the temporal consistency of performance metrics of aggregated hourly wind energy content of the Met Office pan-European Euro4 35+ year Hindcast “brute force” [1] solution have been compared to figures from collocated, multiple-year research met mast anemometers. Annual bias volatility has largely achieved its required ± 3% tolerance without significant overall trends. Using a transparent two-stage linear correction matrix the regularly updated hindcast model was compared to turbine production data at two case study wind farm sites to assess its effectiveness as a consistent, reliable, long-term data source. Independent measurements of ongoing turbine energy conversion performance were delivered, as a low cost interim assessment prior to fully IEC61400 standards compliant verifications. Once impacts of synoptic meteorological icing events and human interventions were accounted for, divergence of model and turbine data was within expected ranges [2] at one site. At the other site a divergence was recorded that is not explained by the data available.

[1] Computationally Efficient Dynamical Downscaling with an Analog Ensemble. Rife D

[2] How does wind farm performance decline with age? Staffell I, Green R

PO.032 – How to improve the energy ramp-up curve with performance assessment results?

Presenting author: Itamar Lessa, Plant Peformance Leader, Casa dos Ventos

Co-author(s): Zaparoli, E.; Caldas, J.; Soares, L.; Mattos, F.; Lima, E.

INTRODUCTION – This work reports the results of a study performed to improve the operational energy output of a planned wind farm using the SCADA data of neighboring wind farm with similar scale and wind turbine technology. It will be shown how an appropriate wind farm performance assessment add value for the asset management and commissioning activities.
APPROACH – After the SCADA data validation process, it seemed clear the effect of bathtube curve in the wind turbines and substation of the project. It was implemented some calculations considering IEC classifications in order to identify and quantify the energy losses impact of the bathtube curve and the creation of key performance indicators
BODY – The wind farms are located in a complex terrain at about 7.5oS latitude. The operational project used to study the pontential improvement of an early performance assessmet has 107 wind turbines and 1 electrical substation 34.5/230kV. The planned one will have 126 wtgs and 1 electrical substation 34.5/230kV. The SCADA data analysis showed that the energy output of the wind farm could improve significantly with a better planning and focusing in some activities that caused high downtimes events.
The efficiency bathtube curve will be defined in terms of downtime and energy in accordance with IEC. The impact of information unavailable will be estimated in terms for the project using the monthly average results.
The presentation will show how the planning activities of the commissioning was improved with the results of performance assessment analysis.
Learning Objectives:
1 – Investigate how the wind farm performance assessment add value for the pre-construction assessment and planning activities.
2 – Compare the effect of a project with a good data recovery and poor one.
3 – Improve the valuation of the project with integrated teams of operational efficiency, commissioning and construction.

PO.033 – A Comparison of Production-based Availability Methods

Presenting author: Francesco Vanni, Senior Engineer, DNV GL

Co-author(s): Michael Wilkinson, Thibault Delouvrié

Wind farm owners, operators and manufacturers are increasingly focussing on production based availability to assess the performance of their assets. The IEC Technical Specifications in 61400-26-1, which define an information model for time-weighted availability, are extended in 61400-26-2 to production-based availability. This provides a framework for establishing the energy shortfall resulting when a wind turbine is non-operative as well as when a turbine is not in full performance (e.g. being de-rated).

A key step in calculating production-based availability is the derivation of potential energy, i.e. the energy that would have been produced given the wind resource were the asset under consideration operating at full performance, during periods of data loss, unavailability or reduced performance.

Under the IEC framework, some high level guidelines are given to calculate the expected energy, with several possible methods defined. However it is important to establish a methodology that is fully specified, robust and resilient to instrumentation changes. This brings direct benefits to the financial and contractual management of the asset, as well as supporting the benchmarking of assets across a portfolio.

To support the definition of such a methodology, the authors have investigated seven different methods for calculating potential energy based on the IEC guidelines by applying them to over 200,000 turbine hours of operational wind farm SCADA data and comparing their performance in terms of a number of indicators.

The paper presents the quantitative results of the study and suggests a practical implementation based on a combination of methods based on average site production and methods based on external wind speed measurements and reference power curves.

Topic 5: Repowering, extending life or decommissioning?

PO.036 – Wind Farm Repowering: A Strategic Management Perspective

Presenting author: Marko Bezbradica, Uppsala University

Co-author(s): Richard Koehler (Thesis Supervisor)

With an estimated wind turbine service life of 20-25 years, it is evident that in the coming years, an increasing number of wind farm owners will have to make a decision between decommissioning and repowering their wind farms. Even though repowering is underlined with a highly complex decision making process, a review of the literature suggests that it is mainly regarded as an engineering feat with a lack of discussion in the strategic and project management context.

The objective of this thesis is to provide a framework that demonstrates the applicability of fundamental strategic and project management concepts on repowering and present a new perspective on this activity with a relatively short and promising history. In an effort to accomplish this, an extensive literature review analyzed different aspects of repowering through the lenses of strategic and project management. These concepts were then combined into the Repowering Strategic Project Management (RSPM) framework to guide the decision maker in selecting and implementing the optimal repowering strategy by establishing a repowering project early in the existing wind farm’s operational life.

The RSPM framework presents a step-by-step guidance tool that demonstrates the process from envisioning an optimal end of service life (EOSL) solution to the repowering execution. In an effort to verify its suitability, the framework has been implemented, demonstrating the wide range of aspects the decision maker has to take into consideration suggesting that an early development of the repowering strategy and its corresponding project could help the owner to repower the wind farm in the most time-efficient manner. Lastly, while the thesis did not emphasize the evaluation and selection of strategy, the implementation of the RSPM framework provided guidelines for these tasks.

PO.037 – New approach for the Condition Monitoring System within Life Extension Strategies

Presenting author: Antonio Fernandez, International R&D projects coordinator, Ingeteam Service S.A.

Co-author(s): Enrique Camacho Cuesta, Jorge Córdoba, Luis Moreno

The energy output from wind turbines has increased dramatically over the past thirty years from 50 kW to 8 MW, while 10-20 MW turbines are currently in the design stage. The increasing numbers of multi-MW turbines being installed offshore require an accurate and cost-effective condition monitoring system (CMS) to be put in place in order to achieve high availability, reliability and maintain profitability of the wind farm.

The ROI (return of investment) for CMS including installation, maintenance and licensing is between 3 and 5 years depending on the wind turbine power. Nowadays these figures are only interesting, from of investment point of view, for turbines bigger than 1 – 1.5 MW of power.

Most turbine manufacturers build their machines with 20-year operational life but in practice around 90% of turbines can potentially carry on working for up to a decade beyond their original operational life.

Assuming a turbine lifespan of 20 years, more than 86 GW of wind capacity is expected to be decommissioned in Europe progressively from 2016. Life extension programs of turbines offer European operators a competitive alternative to repowering in markets where regulated payments have dropped in recent years. These turbines are generally powers lower than 1 MW and it was an unreachable market for installing CMS so far.

Life-extension programs involve the installation of new or additional condition monitoring equipment so it brings the opening of a new scenario for the CMS:

  • Need to install new CMS
  • Need to adapt the actual CMS with more capabilities for the hardware as the adaptability and configurability.
  • Need to have one unique software to integrate the different CMS technologies that they are already installed in the wind turbines

In this paper we will discuss the needs of this new market for the CMS including the installation expectations.

PO.038 – Achieving superior performance and extended asset life-cycle on aging wind assets though re-blading

Presenting author: Carlo Durante, Board Member, eTa Blades


Performance degradation of old wind farms and decreasing incentive tariffs for new projects across Europe disappoint small independent wind-farmers while at the same time leading players pursue asset consolidation to secure long-term portfolios, at the same time requiring longer asset life-cycle and enhanced returns. A Re-blading programme using innovative turbine blades represents an efficient solution for the future of obsolete wind power plants, and an alternative to repowering.

Tendency to substitute specific components such as converters, alternators etc. is visible worldwide already for old wind-farms, while the replacement of blades has only surfaced in case of blade breaks or heavy damages: eTa makes available the option to substitute the rotors, key component determining the performance of a wind turbine.

Re-blading is both a custom and standard solution: it is an innovative blade design targeting superior performance through reverse engineering of the original blade, providing customers with extended asset lifetime and enhanced returns. It can be a standard solution when regarding the most diffused turbine models, or a custom solution in case specific features are required.

Results of re-blading show an enhanced power output averaging beyond +20% vs. the original equipment, a lower O&M cost and, overall, a lower LCOE – thus higher returns for wind-farmers.

During the course of the workshop, eTa Blades will illustrate recent re-blading cases and highlight both technical and financial results achieved with the clients.

PO.039 – Can monitoring systems save your money? And if yes, what about the return of investment?

Presenting author: Heinrich Dyck, Technical Solution Consultant, Phoenix Contact Electronics

Co-author(s): Philipp Dauer

This presentation will show how monitoring solutions can increase the availability and reliability of turbines and reduce finally, thanks to preventing servicing, the costs of energy. Information’s of monitoring systems can be used in a cloud to analyze a typical component or system failure in a turbine fleet. Based on the lightning, rotorblade and actuator monitoring system we will show, how these systems can return their investment in the lifetime of the turbine. For example lightning strikes can cause severe damage and destruction to turbines. The extent of the damage can be evaluated quickly and precisely. Immediate repair and recommissioning of important system functions can prevent consequential damage. As a general rule, it is not possible for employees to continually monitor exposed objects or those with a large surface area, such as remote wind power plants. Damage or destruction is often only monitored once consequential damage has occurred. For this reason, intelligent monitoring systems are used increasingly that permanently monitor the different function states in a system. Monitoring of rotor blades increasingly more important with the trend for operating turbines beyond its lifetime. The rotor blades are subject to large dynamic forces which can lead to structural damages over the service life of the blades. Damages can be recognized early by continuously monitoring loads and vibrations. These data allow a perfect load-based regulation of the wind power plant. If it should ever lead to a damage, this will allow early detection so that it can be removed with little effort. By recording the load spectrum, you monitor the occurring load over the entire service life. Monitoring systems for actuators can give an alarm about an impending yawdrive or pump failure. This enables an immediate response in the event of a malfunction and prevents consequential damage as well as long downtimes.

PO.040 – Life Time Extension (LTE): how to make a reliable estimation about the real accumulated fatigue of the older turbines?

Presenting author: Mercedes Irujo Espinosa de los Monteros, WTG life extension expert, Acciona Energia

Co-author(s): Jose Ramón Fernández Murias

Wind turbines are typically designed for 20-year life. The number of turbines reaching that age will be enormous in the coming years, not only in Spain but also in other European countries. Three options arise: LTE, repowering and dismantling. Red tape, technical constraints and environmental issues are making repowering a non-feasible option in Spain. Additionally, in Europe repowering requires a level playing field, i.e. a common policy at European level within new Renewable Energy Directive.

LTE is the alternative to repowering and extends WT availability and guarantees revenues for additional time. This new business approach needs to be proved. Operators are aware that reliable figures are essential to well-structured end of life plan. Initial experiences show that the weakness of LTE lies in the apparent difficulty of estimating the remaining life of turbines and its related O&M plan.

Wind sector has developed a solid method in the design of new turbines, based on theoretical simulations and prototypes verifications. This approach is proven and accepted by the whole sector. However, when using this proceeding to deal with real cases, results might not explain events registered in the O&M recordings. Those differences have been noted in terms of operation, component behavior and/or joint performance, significantly affecting its fatigue cycle. The consequences of those differences are reflected in the field experiences: unexpected repetitive failures, wearing out earlier than planned and so on. Reliable information about those events is collected by the O&M department via: corrective plan reports, predictive records and failure mechanisms analysis.

Consequently, a consistent turbine tendency has to be based on a combination of the specific turbine information such as wind conditions, operation data and OM records resulting a lifetime estimation with an age margin of 5 years (±2.5years). A theoretical analysis based in aerolastic models could contribute for a further analysis and precise lifetime estimation.

PO.041 – Introducing a multi criteria analysis for wind farm site repowering. A case study on Gotland.

Presenting author: Hans Kerkvliet, Consultant Wind Energy, Bosch & Van Rijn

Co-author(s): Marko Bezbradica, Ivan Montenegro Borbolla, Pyry Lehtimäki, Jonas Armbröster

With an ever-increasing number of offshore wind farms reaching the end of their lifetimes, the decision to either repower or decommission them will be made. Repowering a wind farm may be a financially viable option, as some of the decommissioning and installation expenses can be shared, and the wind resource is well known, which lowers the risk of the project. Furthermore, wind turbine technology has substantially developed over the last decades, and repowering a site can considerably increase production. However, the decision to repower a site is influenced by several technical, economic, environmental or social factors.

Given the many stakeholders (developer, local community, government, etc.) and factors involved, the complexity of the repowering decision-making process is high. Therefore, the use of multi-criteria decision analysis methods provides a valuable tool for decision makers, facilitating a structured framework to identify the best possible option for all stakeholders. In this study, the PROMETHEE II method is applied to the case of Bockstigen, the first Swedish offshore wind farm. Four scenarios were designed, varying the total installed capacity and the number of turbines. Fourteen criteria were defined, including the annual energy produced, capital cost, avian impact and local acceptance. Seven relevant stakeholders (including the developer, local population, and local government) have been identified, and their preferences for all of the criteria have been gathered.

Application of the PROMETHEE II provided a ranking of repowering scenarios, and several key conclusions were obtained. The stakeholders that prefer economic criteria favor scenarios with a higher capacity, while the stakeholders that prefer environmental criteria favor scenarios with a lower capacity. Furthermore, the likelihood of consensus between all stakeholders was analyzed. The findings suggest one scenario with low possibility of consensus, two with medium, and one with high possibility of consensus, which would be the most likely to succeed.

PO.042 – Determining the remaining useful life of offshore wind farms

Presenting author: Nymfa Noppe, PhD Student, Vrije Universiteit Brussel

Co-author(s): Wout Weijtjens, Offshore Wind Infrastructure lab (OWI-lab), Christof Devriendt, Offshore Wind Infrastructure lab (OWI-lab)

To use offshore wind farms as optimal as possible, the optimal usage of the actual fatigue lifetime of a wind turbine and its foundation is crucial. For offshore wind turbines fatigue life is driven by both the quasi-static wind/thrust loads and the dynamic loads, as induced by turbulence and waves. In order to estimate remaining useful life of the turbines in the farm, both contributions need to be well quantified during the turbine’s operational life.

This contribution will show that quasi-static thrust forces can be estimated based on 1-second SCADA data. Since SCADA-data should be available for every turbine, an estimation of the low frequent part of fatigue life consumption can be performed on a wind farm level.

To quantify the impact of the dynamic loads on fatigue life, a couple of well-chosen, representative turbines are instrumented with strain gauges and accelerometers. With measurements of the actual dynamics the dependency of the dynamic load on several SCADA parameters (e.g. turbulence intensity), meteorological data (e.g. wave height) and site specific parameters (e.g. water depth) can be modelled. Once this model is validated among the instrumented turbines, it can be used to extrapolate the dynamic fatigue contribution through the farm.

By combining the static and the modelled dynamic fatigue loads, a farm-wide fatigue assessment can be done. Ultimately resulting in a tool to support end-of-life decisions or optimize O&M. In this contribution we will demonstrate the proposed approach using data from actual Belgian offshore wind farms.

PO.044 – Extending the life of wind farm projects to 40+ years

Presenting author: Alex Olczak, Project Engineer, Wind Prospect

Co-author(s): Robert Speht, Ruben Ruiz de Gordejuela, David Pullinger

For many wind farms, the project life is specified to be equal to the design life of the wind turbine, typically 20 years. The design life of the turbines themselves is specified by the manufacturer and is dependent on components, this is often 20 years. The turbine is then certified for this period. However, the turbine design life and the length of time a project will operate for do not have to be the same, since under some operating conditions, component life may be extended or critical components can be replaced.

The benefits of extending a project life are twofold, firstly an increase in the asset value of the project and secondly a lower overall cost of energy.

Wind Prospect has taken a holistic approach in order to consider the elements of the wind farm which require attention in order to allow a project life to be extended. These include permitting, land lease agreements, OEM warranties, power purchase agreements, tariffs, turbine upgrades and retrofits, and site-specific turbine life analysis. A cost-benefit analysis is performed which considered the impact of an extended life, as opposed to the full repowering of a site.

Our partners, Nabla Wind Power, demonstrated that by considering site-specific operating conditions, component life may be extended, since the operating conditions experienced at a site are often more benign than those for which the components were designed. Operating a wind farm project past its design life will require modification of the operations and maintenance (O&M) procedures, placing a greater emphasis on predictive maintenance. As the project ages, regular inspections will be needed. The lack of OEM warranty during the extended project life may increase the project’s uncertainty; however this can be overcome through the use of an ongoing project certification plan where the condition of the project is assessed at regular intervals.

PO.045 – CBM challenges and opportunities for O&M management of the Offshore Wind Turbines (OWTs)

Presenting author: Jose V.Taboada, PhD Student candidate, University of A Coruña (UCD)

Co-author(s): Vicente Díaz Casás

Extreme operating environment (harsh), the remote location (further), and the specialized access and servicing equipment (barges, ships and boats) needed, offshore O&M costs are expected to be much higher that those for land-based installations towards the H2020.

The O&M costs are known to be a relevant part of levelized cost of energy (LCOE) originated by the offshore wind parks. The magnitude of these costs will be a strong driver in advancements in turbine design and operational reliability. Although, operational costs can be significantly decrease by optimizing decision on applying maintenance strategies, maintenance support organization and follow up maintenance planning. Where reliability availability maintainability supportability (RAMS) and risk based inspection and maintenance analysis (RIMA) philosophies and procedures, are the bases to enhance the life cycle of the OWT’s.

The research work made proposes and suggest mathematical and statistical models to achieve a cost effective maintenance control wind power systems. The aim is to target the economical benefits of condition base monitoring (CBM) applicability that are evaluated for drive train and blades of offshore wind turbines. As well as, to optimize the implementation of the researched maintenance strategies, and to compere the cost-benefit analysis (CBA) of the each maintenance strategies developed.

However, the maintenance models built are calculated with comparative case studies (A and B) and possible scenarios with real environmental, reliability and cost data when available, and sensitivity analyses are performed for the parameters and variables of interest.

In addiction, the LCC analysis (alternatives A and B) targets and identify “Cost Items”(Cost Drivers) that offshore wind energy project carries. Therefore, achievement of a profitable offshore wind concept development is the greatest ambition, but uncertainties rest on maintenance strategies and programs, which ones have showed high cost on early phase of the offshore wind farm development.

Finally, the results prove that the maintenance models can be used to decrease the O&M costs. Where each case studies demonstrate under which conditions the maintenance strategies are optimal, and what is the associated economical risk.

Topic 6: Innovative techniques for enhanced performance

PO.046 – EDF case study: Step by step turbine performance verification and optimisation with a 4-beam nacelle-mounted Lidar

Presenting author: Paul Mazoyer, Application engineer, Leosphere

Co-author(s): Paul Mazoyer, Matthieu Boquet and Florian Rebeyrat

New line of sight ‘s pattern of the Wind Iris leads to a 3D view of the wind field which permits to assess more accurately the wind flow but also to perform high added values calculations from the Lidar. The 4 beams Wind Iris permits to measure the wind speed at two heights for each range gate thus the wind shear can be computed along with the usual values such as the wind speed, wind direction, the turbulence intensity,…

The comparison with a met mast over a simple and a moderately complex terrain is presented showing high agreement between mast and Lidar. 4 beams Wind Iris has been designed to fulfill operational requirement with a strong focus to ease of use and minimizing turbine downtime with quick installation. An operational feedback from EDF is presented with power curve, yaw misalignment and nacelle transfer function computing.

From the wind shear and the turbulence measurement, the power curve can be computed along with sensitivity analysis to shear and turbulence. These computations, in line with the upcoming recommendations for power curve measurement such as rotor equivalent wind speed, are presented. The 3D view of the wind field also permits to get the wind speed at a constant height above the ground level. This allows the accurate wind measurement for moderately complex terrain and open doors to new applications such as the site calibration after turbine erection, saving up to 80% of the cost according to a DNV-GL study [EWEA,2015, Power Performance Testing in Complex Terrain using 3D Nacelle Lidar, poster ].

PO.048 – Performance Index; A quick and efficient way to identify the odd ones.

Presenting author: Bob Smith, EVP – Head of International Business and Investor Relations, Mytrah Energy (India) Ltd

Co-author(s): Vijayamohan S (Mytrah Energy (India) Ltd), Kiran Nair (Mytrah Energy (India) Ltd)

It is essential to spot the under-performing turbines at the earliest possible to avoid energy loss or breakdowns thus reduces the maintenance cost and to enhance the performance. When wind farms are big and aged, handling huge volume of SCADA data (Events and maintenance logs) is a tedious and time consuming task. A simple performance index analysis is developed to identify the odd turbines rather quickly and easily.

If everything good and optimal turbine produces the maximum possible power in any given point of time. Whenever power production capability is influenced by aerodynamic, electrical, mechanical or even controller settings, it directly reflect in the performance. This proposed index evaluate the performance inconsistency and trajectory of a turbine within a wind farm and gives an alert to take deep dive in the issues. The index focuses the accumulation of degradation of the spotted turbine and draws trajectory.

A portfolio of 16 wind farms covering more than 600 wind turbines aged 1 to 8 years and spread across diversified geographical and environmental conditions, are assessed where performance deviation is examined as a macro level function of annual wind turbine generation, generation hours and mean generation of a wind farm or a cluster of wind turbines. To capture the monthly deviation in the performance index rolling year generation is used and each turbine is tagged with performance index. The consistency in temporal and static performances are mapped and compared.

The evaluation of negatively indexed turbine is performed with in-depth SCADA analysis and it was observed that spotted turbines power curve has been suffered due to various performance issues like improper pitching, yaw misalignments, controller settings, curtailment etc., this index will be a key for performance optimization of operational wind farms, root cause analysis, and especially during wind farm acquisitions where huge SCADA data has to be analyzed to evaluate the performance in short time.

PO.049 – Hybrid methodology for Wind Farm Performance Analysis : The complementarity of observation and modelling data.

Presenting author: Laurent Rakoto, Project Engineer, Maintenance Partners

Co-author(s): Dr. Alexis DUTRIEUX (ATM-PRO SPRL), Aurélie BENCHAREL (Eurocape New Energy), Romain FABRE (Eurocape New energy), Thomas GALOPIN (Eurocape New Energy), Philippe MOL (Maintenance Partners), Laurent RAKOTO (Maintenance Partners)

Production optimization and wind turbines availability are two of the main key factors of wind farms project sustainability.

To monitor them, “SCADA” data are typically used. However, one can observe in most cases that some of them show inconsistency such as over/under estimated wind speed, wrongly referenced wind and nacelle directions what may lead to misinterpretations. Rarely, met mast and LIDAR data are available to improve the quality of analysis. Nevertheless, even if they bring more consistency in terms of wind speed and direction, they also show some drawbacks. Indeed, met mast are very often not at the hub height resulting in uncertainties due to wind shear and veer and LIDAR installed on top of the nacelles are sensitive to wake effect and measurement horizon.

To compensate the absence of such tools in most of operating windfarms, we propose to introduce a new monitoring method using local meteorological modelling (based on Large Scale short-term forecast and/or historical re-analysis) considered as a guideline to reconcile observed “SCADA” data.

To validate this new methodology, data from “SCADA”, met mast and LIDAR were collected during about 8 weeks and local meteorological modelling results were produced for the same time period.

Multiple analysis were performed such as time line consistency, data availability, power curve analysis, wind speed distribution, wind roses analysis as well as wake effect analysis.

Local scale model results match very well with the met mast observation as well as with the Hub height observations from Lidar and wind turbine.

This study encourages the approach of building a monitoring system combining observation data with data generated by the local meteorological modelling in the goal of optimizing wind farm performance and availability. As perspective, further validation exercises should be performed on other wind farms and considering longer term time period data.

PO.050 – Turbine performance evaluation with ground-based and turbine-mounted lidar

Presenting author: Matt Smith, ZephIR Sales Manager, ZephIR Lidar

Co-author(s): Michael Harris, John Medley, Muhammad Mangat, Mark Pitter, CarloAlberto Ratti, Chris Slinger, Scott Wylie

A viable approach to turbine performance enhancement relies on full characterisation of an individual turbine during operation to identify possible underperformance issues. These problems might include yaw misalignment, blade degradation, incorrect controller settings etc. Lidar offers a powerful and flexible tool for troubleshooting of problematic turbines, pre-empting potential failures. The increased detail obtained on the wind field also allows problems due to the turbine itself to be distinguished from those caused by external factors such as terrain, forestry, shear, inflow angle, etc.

This paper describes a case study in the UK on an operational wind farm on a moderately complex upland site with some forestry. A ground-based wind profiling lidar (ZephIR 300) was combined with a nacelle-mounted lidar (ZephIR DM) to investigate the baseline performance for a 2.3 MW turbine, with a rotor diameter of 83 m and a hub height of 65 m, that was believed to be performing well. The impact of the ZephIR DM lidar on the turbine’s existing nacelle anemometry was investigated and found to be negligible. Comparisons showed excellent agreement between the two lidars for appropriate sectors, providing high confidence in the results from both instruments.

The lidars enabled an investigation of the effects of site complexity and inflow angle. Power performance evaluations were performed; a shortfall of approximately 4% in energy production was measured in comparison to the manufacturer’s power curve, even for this “good” turbine, indicating scope for improvement. A significant yaw misalignment of 3.7° was found, which may have contributed partially to the underperformance. Other possible factors include component wear and turbine ageing, and the effects of terrain. The lidar measurements included some at shorter ranges (e.g. 1D) than those used for IEC compliant power curves, to investigate the reduction of terrain effects and decouple them from turbine-related factors.


PO.051 – Characterization of wind turbine noise applied to predictive maintenance

Presenting author: Adão Muniz, Engineer, Chesf – Companhia Hidrelétrica de São Francisco

Co-author(s): Samuel Araújo Lima; Francisco Ilson da Silva Júnior; Adão Linhares Muniz; Marlos Diógenes Lucas; Paulo Henrique Pereira Silva.

With the rapid expansion of wind power during the beginning of 21st century in Brazil and worldwide, many wind turbines of different and innovative technologies began operations. Many of the environmental and operational consequences of this expansion are still being studied and evaluated. Among the environmental consequences, one can mention the noise produced by larger diameter wind turbines, whose frequencies are often not audible, although perceptible to the human brain. In this work were made measurements of the noise associated with wind turbines in the state of Ceara. It was initially made the characterization of wind turbine noise, identifying sources, frequencies, composition, intensity and impacts to health. Experimental measurements of sound in large wind generators were made in direct-drive wind turbine generators, in the city of Aracati, State of Ceara, in the light of the international standard IEC 61400-11, documenting the methodology applied in a manner that is easily replicated. The experimental results were processed and analyzed according to the standard. Filters were applied in order to identify the frequency and types of most significant noise in the experiment, comparing them with the literature. The procedures performed and documented may be applied commercially to perform noise measurements under international standard, and in future studies applied to predictive maintenance and environmental engineering.

Topic 7: Offshore operations: lowering the costs

PO.053 – Using Offshore Remote Environmental Monitoring to Lower Operating Costs

Presenting author: Francois Berry, Account Manager, AXYS Technologies

Co-author(s): Graham Howe, Robin Thomsen, Breanne Gellatly

This abstract will demonstrate how remote environmental monitoring will play a key role in making offshore wind farms a success in years to come. Ocean data acquisition systems that accurately record & transmit meteorological and oceanographic data in near real time equip developers with information needed to make the best decisions throughout the project lifecycle. The initial wind resource assessment data can be gathered from a floating LiDAR instead of a meteorological mast to significantly reduce costs of the 12-month data collection campaign. Following the acquisition of assessment data, meteorological and oceanographic data buoys can be used for engineering design criteria, throughout the construction phase and for the ongoing operations and maintenance of the offshore wind farm.

Accurate weather data helps to control expenses and protect assets by understanding current weather information and increasing knowledge of local marine environmental conditions. This timely information improves vessel traffic management and safety at sea by being aware of potential hazards such as increases in winds or wave heights. At each stage of development, real-time environmental data helps to significantly improve yields and reduce costs.

Attendees of the presentation can expect to leave with a better understanding of the various types of ocean data acquisition systems available, what and how they measure, their survivability in rough seas throughout winter months, and how recorded data is shared and presented to the decision-makers so they can use it to control expenses in a variety of ways.

Topic 9: Lowering the costs of important correctives measures

PO.056 – Crane less large correctives to reduce by 25% turbines’ maintenance costs

Presenting author: Israel Alonso Bravo, Wind Turbines Technical Trainer Specialist, Gamesa

Co-author(s): Borja Pielago Lopez, Christian Jourdain

Changes in incentive schemes are challenging wind turbines servicers to get O&M costs further down. As the major OPEX cost faced by asset owners are due to large correctives, turbine manufacturers propose CMS solutions, tools and working procedures to perform repairs up towers. Still, some large components have to be repaired in plants, causing significant downtime and losses of revenue. One of the major remaining challenges lies in cranes’ availability and costs, either because towers are getting taller and components heavier, either because cranes are not a commodity product. Although turbines’ specific solutions exist, asset owners, as well as Gamesa, investigated, developed or tested multi-brand tools to avoid the need for any crane.

Generators were the first components to benefit from crane alternative and compact solutions. Hoist, cables, motors and the new generator could fit in just one container reducing also logistics cost but these solutions are not always a no-brainer choice as they still require more staff and for longer time than standard solutions.

As gearboxes are one of the heavier components of the nacelle, the add-on hoist must be solid but also well designed to transfer appropriately loads and moments to the turbines structure when the gearbox is extracted from the nacelle and goes down by the side or backside of the nacelle. Either reusing existing nacelle beams, or appending directly itself to the tower, all solutions are complex and require a load analysis.

Blades are getting longer to gain efficiency and generate more output, making necessary two large cranes to change any blade. Weight and structural constrains prevent a complete crane less solution but using one instead of two, generates already significant savings.

Gamesa will propose design improvements to facilitate the development and use of multi-brand and multi-components solutions, reducing operational expenditures.