Table of contents

Preface

On behalf of the European Academy of Wind Energy (EAWE¹) and WindEurope (formerly the European Wind Energy Association EWEA), we hereby have the pleasure of presenting the Scientific Proceedings of the WindEurope Conference 2018.

Global Wind Summit 2018 (WindEurope Conference & WindEnergy Hamburg) took place in Hamburg on 25-28 September 2018. It is one of the largest and most important meeting places of the wind energy community. This year's conference has featured 50 thematic sessions with a total of more than 500 speakers. As in previous years, the sessions mixed industrial content with scientific works, in order to increase the visibility of relevant scientific research and to facilitate an interchange of ideas between industry and academia.

In continuation of the successful agreement between WindEurope and IOP Publishing, the scientific contributions of the WindEurope Conference 2018 are published in the Journal of Physics: Conference Series, an Open Access journal managed by the Institute of Physics (IOP). All papers in this volume originate from scientific contributions presented at WindEurope Conference 2018, and have been peer-reviewed in order to ensure strict, international standards, coordinated by the Scientific Proceedings Editors and aided by the EAWE Wind Europe Scientific Committee.

New this year was the possibility for every accepted scientific abstract to submit a paper for the Scientific Proceedings. In previous years only the scientific papers presented in oral sessions were given this opportunity, but this year authors could submit a manuscript also for accepted scientific poster presentations. We believe this is an important development that benefits our community, and that greatly increases the attractiveness of WindEurope Conference. In particular, this guarantees long-term storage and easy electronic reference of conference papers, and we thank WindEurope for making this possible. Of course this positive development has also meant a much higher workload than previously. This year, a total of 46 original papers were submitted, of which 40 were eventually accepted for publication.

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the proceedings Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

The evaluation and comparison of reanalysis datasets (NCEP-CFSR and ERA-Interim) against mast measured wind data for Keti-bander port of Pakistan have been performed. In the last decade, wind farms have been developed on the land, but there is still need for the development of offshore wind farms on the 1100 km coast of Pakistan. The wind data measured at the Keti Bandar Port of Pakistan at different heights for the duration of 20 months has been used in this study. The evaluations of satellite datasets against measured data were done based on statistical analysis, monthly mean time series and Weibull probability distribution function. The wind data at 30 m, 60 m and 85 m was extrapolated using the Logarithmic law from 10 m height. At 30 m height both satellite datasets show very good agreement with measured data, the predictions of CFSR data are much better than ERA-Interim. The percentage difference for mean wind speed, wind power density and Weibull parameters at 30 m are less than 5%. Overall NCEP-CFSR gave better results compared to ERA-Interim. These results may be used for the offshore wind resource assessment for Pakistan due to unavailability of offshore wind speed data.

As wind turbines are getting larger and cost reductions through up-scaling are reaching a limit, there is increasing pressure to reduce their installation and operating costs, making the business case for Vertical Axis Wind Turbines (VAWTs) more interesting again. However, in order to properly assess the economic potential of large-scale VAWTs, improved design tools are required. As the research budget for VAWT projects is generally too small to carry out expensive large-scale wind tunnel tests and field measurements, alternative methods are required. In this work, the application of small-scale, lower budget methods for improving VAWT design tools is assessed. It is shown that (a) currently available tools for VAWT design have not been sufficiently validated, (b) lower budget, small-scale wind tunnel tests can be effective for examining VAWT performance in terms of average power coefficient vs. tip speed ratio as well as the dynamics of the torque, and (c) Detached Eddy Simulations on small-scale VAWTs can be effective for examining their performance in terms of average power coefficient vs. tip speed ratio as well as the forces on the blades. Based on these results, a process for the transfer of the results of lower budget, small-scale measurements and simulations into recommendations for improved design tools is being developed.

The increase in wind turbine size during recent years has led to a situation where the wind speed measured at hub height is no longer a sufficient representation of the power available to be extracted by a turbine. Light Detection and Ranging ("Lidar") wind sensing devices can measure wind speeds in a volume in front of the sensor, offering affordable and improved estimation of wind turbine power performance and loading. However, a Lidar can only measure the component of the wind velocity in the direction of the beam. This makes reconstruction of the wind velocity field from raw Lidar measurements a challenge, and current methods contain assumptions which cause inaccuracies in complex terrain and in wind turbine wakes. In addition, data availability is reduced in specific weather conditions, such as very cold climates and dense fog. A novel Machine Learning method is developed here, based on Gaussian Process regression, to remove these assumptions when producing full 3D wind fields from Lidar measurements. This approach is naturally robust to overfitting and predicts uncertainty derived from data density and machine error, without needing physical information about the local terrain. Initial validation by comparison of a Windcube Lidar with a meteorological mast, on a site with simple conditions, shows excellent performance which meets the threshold for commercial use. The method also infers data during measurement gaps, offering the potential for 100% data availability. Instantaneous 2D wake measurements in a plane can be made, which when validated and further developed will offer a breakthrough in understanding of wind farm interactions and turbine loading.

This study aims to evaluate reanalysis, analysis and forecast data of wind speed and direction with the surface measured data at a site in Jhimpir region of Pakistan. Five datasets (reanalysis, analysis and forecast); NCEP-NCAR, 20th Century Reanalysis v2c (20C), CFSR, GFS and NCEP-FNL have been used for this study. The comparison has been made on six hourly and daily bases. The statistical parameters used are Mean Bias Error (MBE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and correlation coefficient (R). The Weibull probability distribution has been drawn, the shape and the scale factors have been calculated. The CFSR data shows significantly good results for lower temporal resolution (daily) with a high correlation coefficient for a wind speed of 0.898 while at a higher temporal resolution of 20C shows significantly lower values of MBE of -0.87 m/s and CFSR shows lower values of RMSE of 2.09 m/s. CSFR wind direction data show good agreement with measured data in terms of statistical parameters The wind industry in Pakistan is under development stages with the possible potential of the offshore wind farm and expansion of land wind farms in other areas of the country, this study will be an initiative toward the initial wind resource assessment for potential sites in the wind corridor.

In this study we present the ability to detect wakes in the inflow of turbines using nacelle-mounted continuous-wave lidar systems. Wake flows generate small-scale turbulence, which has significantly smaller length-scales than ambient turbulence. Due to the lidars large probe volume this turbulence is attenuated and will not be visible in the lidar's measurements. One approach to retrieve information about small-scale turbulence is by measuring the lidar Doppler spectrum width. Here we present an wake detection algorithm based on these measurements at two distinct locations in front of the turbine. By comparing the line-of-sight turbulence intensity and considering the instantaneous misalignment it is possible to detect half-and full-wakes. This has been tested during a 4.5 month long experiment and results show that situations where the wake affects the lidar measurements can be removed.

As a part of the New European Wind Atlas project, we investigate the estimation of extreme winds from mesoscale simulations. In order to take the smoothing effect of the simulations into account, a spectral correction method is applied to the data. We show that the corrected extreme wind estimates are close to the values obtained from offshore met masts. Hence, after further investigations we plan to use the examined approach as a basis for the calculation of extreme winds on the complete New European Wind Atlas, which will be publicly available at the end of the project.

In the present study it is discussed a sensitivity analysis on input parameters of a CFD resource assessment methodology built on top of OpenFOAM 4.1, a well-known open source library for numerical fluid dynamics. RANS are solved for dry uncompressible air, the Atmospheric Boundary Layer is calculated without thermal effects (neutral conditions). It is highlighted how the control of a metric based upon a weighted root mean square error (wRMSE) of the local accelerations (speed ups) can guide the wind analyst in the design of the computational mesh and further numerical settings. Moreover, it will be quantified the wRMSE as a function of the distance to the measurement points. The parameters analysed are the horizontal extension of the model, the horizontal resolution within the refined area, which is covering the layout of the wind farm, three different versions of k-ε turbulence closure and the number of directional sectors considered.

Atmospheric stability significantly influences the characteristics of a wind resource and strongly affects wind turbine power production and structural loads. Stability is governed by the thermal structure of the atmospheric boundary layer (ABL). Unstable ABLs are convective and increase turbulence, but reduce vertical wind shear, while stable ABLs reduce turbulence and increase wind shear. In neutral ABLs mechanical effects of terrain and roughness dominate.

The Monin-Obukhov length (MOL) and Richardson numbers are the recommended methods to quantify atmospheric stability. These methods require advanced and expensive measurements of temperature differences or 3D-sonic covariances, not installed on standard wind power masts.

This study presents a novel methodology to quantify stability based only on standard wind measurements. At high wind speeds turbulence and wind shear converge to the neutral ABL response in a given direction while the relative deviations of shear and turbulence at lower wind speeds strongly correlate with stability. When normalized by the neutral shear and turbulence, these deviations directly quantify stability. Here we present a novel method to estimate MOL directly from the ratio of normalized shear and turbulence.

The proposed method to quantify stability from standard wind measurements, provides an important input to advanced wind flow modelling of stability effects to improve the accuracy of predicted power production and structural loads.

Lidar-assisted control is a promising technology for reducing structural loads on wind turbines. Guidelines for certifying wind turbines with this technology are important for its widespread adoption. As a first step, an IEA Wind Task 32 workshop was held, bringing together wind turbine manufacturers, lidar suppliers, certifiers, consultants, and researchers to identify barriers to certification with lidar-assisted control and ideas for mitigating the barriers. This paper builds on the outcome of the workshop by providing an analysis of the areas affected and the remaining challenges. Further, initial best practices are given to address the challenges, covering the lidar system, control and protection systems, design loads, and type testing.

In this study the performance of the Weather Research and Forecast (WRF) model in a complex and coastal terrain has been evaluated with focus on wind resource assessment. The study area is a small community on the northern part of the island Senja, Norway. The community, with fishery and seafood as its main industry, is being limited by poor grid connection. One of the solutions is to increase the production of local power from wind energy. There are no in-situ wind measurements in the area, and therefore numerical weather prediction models, namely the WRF model, is being evaluated as a method for wind resource assessment. The WRF model has been run for the whole of 2017 with high resolution covering an area large enough to include the three closest weather stations. The model is compared to the observed wind speed and direction. It is found that the model is able to reproduce the average wind speed and wind direction quite well for two of the locations, while for the third location the average wind speed is considerably overestimated compared to the observations. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) found are larger than in other comparable studies.

In this work three different numerical methods are used to simulate a MW class wind turbine under turbulent inflow conditions. These methods are a blade resolved Computational Fluid Dynamics (CFD) simulation, an actuator line based CFD simulation and a Blade Element Momentum (BEM) approach. For all three methods sectional and integral forces are investigated in terms of mean, standard deviation, power spectral density and fatigue loads. It is shown that the power spectral densities of integral forces are in good agreement in the low frequency range for all methods. However, deviations are observed from 2 Hz onward. Although the fatigue loads of the CFD based methods are similar for the torque, the loads from BEM differ by 22%. For the thrust BEM only deviates by 4.5% from the blade resolved case. Nevertheless the actuator line based simulation differs by up to 7.3%. The standard deviations of sectional forces for all three methods relate very well to the standard deviation of integral forces. Nevertheless, a similar relation for the fatigue loads could not be observed.

The national funded WindforS project VORKAST investigated the use of a long-range lidar for very short-term power forecasting of a wind turbine in complex terrain. This ability is essential for the grid integration of large amounts of wind energy. This paper describes the process of setting up the lidar, data handling, and wind field reconstruction. A process based on Taylor's frozen turbulence hypothesis is used to propagate wind speeds to the turbine and to forecast wind ramps. The lidar-based forecast is currently less accurate than persistence in these conditions. It is expected that the use of a more realistic propagation model will improve the forecasts in such complex terrain.

This work presents a sequential approach to explore and optimize the benefits of lidar-assisted control for wind turbines. The optimization is divided in three steps: lidar hardware, lidar data processing, and feedback controller optimization. Appropriate optimization criteria and computational efficient models are used for the intermediate steps and energy production is optimized in the last step with a full aero-elastic model to provide an estimation of lidar-assisted control without the need of a detailed cost model. The case study shows that lidar-assisted control together with an adjustment of the power level are promising to extend the life-time of wind turbines and finally increase the energy capture.

This study presents two numerical multiphysics models of the NAUTILUS-10 floating support structure mounting the DTU10 MW Reference Wind Turbine at Gulf of Maine site, and analyses its dynamics. With the site conditions and the FAST model of the onshore turbine as the starting point, the floating support structure: tower, floating substructure with its corresponding active ballast system and station keeping system, was designed by NAUTILUS. The numerical models were developed and the onshore DTU wind energy controller was tuned to avoid the resonance of the operating FOWT by TECNALIA, in the framework of H2020 LIFES50+ project. This concept and its subsystems are fully characterised throughout this paper and implemented in opensource code, FAST v8.16. Here, the mooring dynamics are solved using MoorDyn, and the hydrodynamic properties are computed using HydroDyn. Viscous effects, not captured by radiation-diffraction theory, are modelled using two different approaches: (1) through linear and quadratic additional hydrodynamic damping matrices and (2) by means of Morison elements. A set of simulations (such as, decay, wind only and broadband irregular waves tests) were carried out with system identification purposes and to analyse the differences between the two models presented. Then, a set of simulations in stochastic wind and waves were carried out to characterise the global response of the FOWT.

Offshore wind farms are progressing further offshore and into deeper waters, presenting the need for new substructures, including floating offshore wind turbines. These floating turbines will require dynamic cables to run through the water column, exposing them to the dynamic loadings of the marine environment. This paper presents a tool which models the stresses across a dynamic cable cross section's insulation layers when attached to a floating wind platform. Differing wave, wind and current flow conditions are applied and their impact on the stress distributions of the dynamic cable's insulation layers are presented. Finally from these stress histories, accumulated fatigue damage of the insulation is calculated and presented. The outcome of this can be used to estimate fatigue damage of a cable components cross section at any point along the cable length, and aid in cable installation configuration decisions.

Wind turbines are subject to fatigue loads during their entire lifetime of 20-25 years. A main source of the fatigue loads is the turbulence, which varies with direction due to the surrounding terrain and wake effects inside wind farms. A common approach to assess wind turbine fatigue loads is to simulate the structural response based on a site-specific wind climate, described in the IEC 61400-1 standard. To reduce the amount of needed simulations the standard introduces an "effective turbulence" approximation that integrates directional variation of turbulence, resulting in an omnidirectional value. This method implicitly assumes that all wind turbine components face the wind directly, which is a conservative simplification for components below the yaw bearing.

Using wind measurements from almost one hundred international sites, we show how this simplification leads to over-predictions of tower fatigue loads of up to 23% compared to directional fatigue accumulation. Three simplified models are developed to approximate the directional fatigue damage using various levels of information ranging from only the wind rose to full sector wise simulations. The first two recommended models may be used as proxies to decide if sector wise simulations are feasible, and the last model accurately predicts the full directional fatigue damage. The simplified models can contribute to a reduced material consumption of wind turbine towers, thereby reducing the cost of wind energy.

In this work a new design of multi-pole gearless low-speed Generator with Magnets on the Stator (GMS) for wind turbine is described. Gearless GMS combines both high number of magnetic poles created by magnets and low-pole winding creating strong electromotive force. Therefore GMS has high efficiency and low operational speed. The GMS mathematical model has been developed. The low-speed gearless GMS was designed with the help of the developed mathematical model. Comparison of the designed GMS with a generator with magnets on the rotor (SG) is given. The GMS active material cost is 2.3 times less than that for the SG. The GMS mass is 1.3 times less. The GMS has higher efficiency at the rated speed. Also GMS maintain high efficiency in wide range of torques and speeds and GMS torque ripple is low.

The interaction between nearby wind turbines in a wind farm modifies the power and loads compared to their stand-alone values. The increased turbulence intensity and the modified turbulence structure at the downstream turbines creates higher fatigue loading, which can be mitigated by wind farm and/or wind turbine control. To alleviate loads and maximize power possible strategies such as wake steering, where the turbine is yawed to redirect the wake such that it does not impinge the downstream turbine, have been studied. The work presented here focuses on situations where the wake is nevertheless affecting the downstream turbine, and more specifically how high loads can be avoided by yawing the wake-affected turbine. The analysis is conducted on a 2.3 MW machine, and the flow field is simulated using the Dynamic Wake Meandering model. The study investigates the impact on power and loads for different longitudinal interspacing and turbulence intensities. Optimal yaw strategies are defined for above rated regions where no power loss occurs. The potential load alleviation for different load sensors are studied, but the presentation is focussed on the blade root flapwise fatigue loading. For full wake at 3D interspacing and turbulence intensity of 5 %, around 35 % of load reduction on the 1 Hz Damage Equivalent Loads can be achieved at high wind speeds. Smaller reductions are achieved for higher atmospheric turbulence; the analogue case with 15 % turbulence intensity shows 17 % potential alleviation. The alleviation on the wind turbine lifetime is also calculated and compared for different turbulence intensities and mean wind speeds. Small reductions are achieved for sites with low mean wind speed and high turbulence intensity, but high reductions, of around 19 %, are accomplished in low turbulence intensity with high mean wind speed.

Traditional Danish concept wind turbines face many constraints when upscaling in order to access higher wind speeds, such as size, mechanical loading and weight. It is possible that some of these constraints could be circumvented through use of airborne wind energy systems (AWES).

With research into AWES becoming more prominent, the topic of launching and landing the system must be analysed in detail. Currently several concepts are being pursued with differing launch and land technologies. For all systems it is likely that minimising launch and land cycles will be a key objective due to increased energy costs and hardware risk in these phases.

This research focuses on a cross-wind ground-based generation system and discusses the problem of the launch and land policy with regards to the wind speed at operational height. The paper also discusses the use of an airborne powered loiter phase and a grounded waiting phase. A key consideration when analysing this problem is wind speed measurement uncertainty (including the degree of temporal averaging) and how to integrate this uncertainty into any launch & land policy.

The present research concerns cost-benefit analysis with respect to generated and consumed energy cost functions for each flight phase. It is found that for any given AWES there will be an optimum airborne loiter time after which a system should be landed. This avoids landings due to short-duration low wind periods.

This research will be followed up by further analysis of additional cost functions such as reliability and failure aspects associated with each of the above phases. Further research will also consider the impact of short term forecasting of various accuracy levels on the optimal control policy and performance of AWES.

This contribution deals with the state observability and parameter identifiability analysis for nonlinear wind turbine control (WTC) systems based on empirical observability Gramian (EOG) matrices. The concepts of observability and Gramian matrices are introduced to investigate the inverse condition number (ICN) and the singular value decomposition (SVD) of the EOG matrices and to evaluate different sensor configurations with respect to their degree of observability. The obtained results are then reviewed for practical plausibility over state estimates, provided by sigma-point Kalman filters (SPKF), in order to relate the observability measures directly to the expectable estimation error. The investigation reveals indeed a correlation between the employed measures for individual state observability and the estimates produced by the nonlinear filters. The joint assessment of ICN, SVD and SPKF results is found as a strong tool when aiming at a holistic and practically relevant observability discussion.

Modern wind turbine blades are being tested for certification purposes in accordance to the IEC-64100 standard. Part 23 of the norm details the requirements for the full scale structural testing of rotor blades. As a minimum, it requires measurement of the first and second flap wise and first edge wise natural frequencies. It lists damping and mode shapes as other blade properties which may be of interest and optionally measured. The paper presents the modal model parameters estimation based on the experimental modal analysis. In two tests performed, the input force has been introduced through impact hammer and two electrodynamic shakers excitation. Several first modes had been identified for both excitation methods, including first torsional mode of the investigated blade. Results of the modal tests can be used to (a) provide more detailed information about the structural dynamics characteristics of the blade and (b) improve the design by adjusting the dynamic properties of the blade to some desired condition.

Floating wind turbines offer the potential to harness the considerable wind energy resource located at deep water offshore locations. Accurate numerical modelling of floating wind turbines is of utmost importance given its prominence in the design process. DNV GL's aero-hydro-servo-elastic modelling package 'Bladed' was one of the tools validated as part of the Offshore Code Comparison Collaboration Continuation with Correlation (OC5) project [1] and gave favourable results alongside the other participants. However, in common with all of the participants using a Boundary Element Method hydrodynamic approach, the majority of the loads were under-predicted (whilst over-predicted by Morison-only approaches). In particular, the low frequency excitation was not fully captured in the Bladed numerical simulations. This paper describes the implementation and results of new simulations in which additional modelling features are implemented in the DNV GL Bladed OC5 model. The results show that including instantaneous hydrostatics and Froude-Krylov forcing produces a better match with experimental spectral energy density for platform pitch and surge motion, which in turns leads to improvements in tower base shear force predictions.

Innovation in the wind turbine's drivetrain are mainly motivated by the goal to have better products. To have an improved final product, it should be analysed in a holistic manner over the drivetrains lifetime. One essential lifetime phase of a wind turbines drivetrain is the manufacturing phase, which is focused in this analysis. This paper presents a way to estimate manufacturing cost of wind turbine drivetrains at an early design phase. The approach is based on literature and expert interviews as well as their abstractions. The target audience are people involved in the development of new wind turbine drivetrain concepts. To customize the approach for their requirements, it is based on a minimum number of necessary input mainly geometric component specification. This approach is modular, scalable and applicable on to future drivetrain concepts. The used approach proves to be an effective way for estimating manufacturing costs of drivetrain components. A comparative analysis against a benchmark application, a 5 MW wind turbine's drivetrain, confirms the accuracy of the presented approach. A case study dealing with two possible gearbox solutions with a power rating over 5 MW underlines the importance of taking manufacturing cost in consideration when thinking about new developments in wind turbine drivetrain technology.

The SCADA system for wind turbine often logs data at 10 minutes time step, mostly due to the technical constraints. However, with the developpement in measurement and storage technology, the collection of data with higher sampling frequency is feasible. The question about an optimal time step for SCADA data is then become interesting. Our paper aims to answer this question through a statistical analysis of the power curve at different time step. In order to explain and confirm the results of this study, a spectral analysis is performed. Both approaches indicate that the time step of 10 minutes is still the best choice as it gives the best predictability of the output power from wind speed.

As more and more wind turbines are coming close to the end of their design lifetime, evaluation of end of life strategies is becoming highly relevant. Moreover, as turbine technology matures and wind farms grow larger, lifetime extension becomes a financially attractive option compared to re-powering and decommissioning. Present work suggests control strategies, namely down-regulation and individual blade control, as lifetime extension enablers. The concept of using them as retrofit control implementations is explained. Their individual and combined potential in fatigue load reduction is evaluated, along with their effect on other performance and pitch system metrics. Finally, the possible period of extension, beyond the nominal 20 years, is evaluated in an example case where the retrofit control strategy is applied after 15 years of baseline operation. The aeroelastic simulations are performed with a 10 MW reference wind turbine, according to load certification standards. Results show that the two methods complement each other in load alleviation. The pitch actuator demands are also significantly decreased when the two methods are combined.

According to the Contracts for Difference (CfD) scheme introduced to support the deployment of offshore wind installations, an electricity generation party is paid the difference between a constant "strike price" (determined be means of a competitive auction) and the average UK market electricity price for every MWh of power output produced. The scheme lasts for 15 years, after which the electricity output is sold on the average market price. To this end, estimating the long term profitability of the investment greatly depends on the forecasted market prices. This paper presents the simulation results of future electricity prices based on three different simulation methods, namely: the Geometric Brownian motion (GBM), the Autoregressive Integrated Moving average (ARIMA) and a model combining Mean-Reversion and Jump-Diffusion (MRJD) processes. A number of simulation paths are generated for a time horizon of 10 years and they are introduced to a fully integrated techno-economic model developed by the authors. As a result, joint probability distributions of the NPV derived from the three different methods are presented. This study is relevant to investors and policy makers to check the viability of an investment and to predict its stochastic temporal return profile.

The installation of new electrical power plants from renewable sources is key in the transition towards a low-carbon economy. An important amount of diverse raw materials is required for this development. Due to its current prominence among renewable energy sources, we assess the expected development of wind energy towards the availability of the required raw materials up to 2050. Wind power is found to be in a favourable position, over solar thermal and photovoltaic power. Among the two main wind turbine technologies, the installation of direct drive turbines with permanent magnets faces a more challenging future. Recycling is an important strategy to simultaneously reduce risks and costs.

China continuously maintains the first place of global wind energy with the national installed capacity of 188GW at the end of 2017, accounting for over 34.8% of the total world capacity. With the continuous increase both in number and height of wind turbines, the spatial planning has the task to provide suitable places for wind farms. Thus the rising demand for good locations is increasingly causing conflicts. The "13th Five-Year-Plan" of China aims to optimize the spatial layout of wind energy, resolving wind curtailment problems in North China and encouraging the construction of distributed, low-speed wind farms in South China for consumer near energy production. The ecological and social impacts caused by wind farms become more prominent in the densely populated areas of South China, which brings challenges to spatial planning and land use coordination. As a pioneer of wind industry, Germany is faced with similar problems and very early paid attention on spatial planning issues like wind farm site selection, environmental protection and land use planning. This paper compares the spatial planning systems of two countries and draws experiences from Germany to optimize the Chinese wind farm planning procedures. Planning principles and specific planning procedures for the integration of wind farm and spatial planning both in regional and local levels will be proposed according to the developing status of China. An on-shore wind farm planning framework will be set up implemented at each planning level, and coordinated with other land use and space functions to ensure the synchronous development of renewable energy and surrounding ecological and human environment.

With single elements weighing up to hundreds of tonnes and lifted to heights of 100 meters, offshore wind turbines can pose risks to personnel, assets, and the environment during installation and maintenance interventions. To increase safety during offshore lifts, this study focuses on solutions for human-free lifting operations. Ideas in the categories of logistics, connections, as well as guidance and control, were discussed and ranked by means of a multi-criteria decision analysis. Based upon 38 survey responses weighting 21 predefined decision criteria, the most promising concepts were selected. Logistically, pre-assembled systems would reduce the number of lifts and thus reduce the risk. A MATLAB-based code has been developed to optimise installation time, lifted weight, and number of lifts. Automated bolting and seafastening solutions have high potential to increase safety during the transport of the wind turbine elements and, additionally, speed up the process. Finally, the wind turbine should be lifted on top of the support structure without having personnel being under the load. A multi-directional mechanical guiding element has been designed and tested successfully in combination with visual guidance by cameras in a small-scale experiment.

With the total 600MW power production capacity, Kriegers Flak will be the largest offshore wind power plant (OWPP) in Denmark. Kriegers Flak will utilize the two unequal sections, 400MW and 200MW, on the two offshore platforms interconnected via a 9 km 200kV cable and connected to the onshore substation via two 80 km 220kV cables. From the onshore 220kV substation, the 220kV connections continue to the two different 400/220kV substations of the Danish transmission grid. From the 400MW offshore platform, the connection continues to the 150kV offshore infrastructure of Germany. The Kriegers Flak grid connection resamples a meshed offshore grid (MOG) which increases complexity of and requirements to its overall voltage and reactive power control. This presentation describes how the overall voltage and reactive power control system is proposed and designed for optimized operation and reduction of the stress and efforts on the control equipment of the Kriegers Flak 220kV system.

With increasing levels of electrical energy generated by intermittent sources such as wind turbines, their participation in grid ancillary services is becoming a necessity. Typically, all generated energy from variable generators is absorbed by the electric grid and balancing is left to traditional generators. Wind turbine technology has matured to the level where a large wind generator is capable of providing ancillary services such as up- and down-active power regulation (secondary frequency regulation). The up-regulation capacity of a variable generator is constrained primarily by external factors such as the prevailing wind speed in the case of a wind turbine. This work uses the Wind Energy Institute of Canada's (WEICan) 10 MW Wind R&D Park (Type 5 generators) in Prince Edward Island, Canada, to test and evaluate a simple algorithm to provide up- and down-regulation services from a wind park. The developed algorithm uses a 10-minute averaged wind speed to estimate the available park generation potential. A fixed power curtailment is applied to provide room for up-regulation. An historical, external AGC signal is then applied to the wind park's active power set-point and the resulting park performance is evaluated. Results of the 4.5 hour test prove the technical capability of the wind farm in participating in the regulation market. A performance score of 64 % was calculated according to the PJM method, averaged across the test duration.

Diesel Generators (DG) are commonly adopted to supply the critical auxiliary loads for Offshore Wind Farm (OWF) during islanding operation. To reduce fuel consumption, avoid over-sizing of DG, and further enable a smooth resynchronization to main grid, a hybrid Auxiliary Power Supply (APS) system is designed with a combination of DGs, Wind Turbine Generators (WTGs), and battery Energy Storage System (ESS). Different from the typical industrial solution, this hybrid APS system uses not only DGs, but also WTGs to supply part of the auxiliary load when there is wind blowing for reducing fuel consumption and the corresponding refuelling works; moreover, the wind turbine converters can provide reactive power for balancing the charging power from the cable array inside the OWF, so as to avoid the oversizing of DG itself. ESS are also introduced to further reduce the dependence on the DGs. With enough capacity of ESS, it is even possible to remove DGs while still be able to fulfil the requirement on auxiliary load supply during islanding mode.

In this paper: firstly, the cost effectiveness of such hybrid APS is discussed via techno-economic analysis; secondly, two types of hybrid APSs with coordinated hierarchical control architectures are introduced, as well as the control strategy design for both centralized and distributed controllers; thirdly, simulation models are developed in MATLAB/Simulink, where two types of models are included. They are phasor-type model for centralized control strategy verification, and average-type model for distributed control strategy verification. The performance of hybrid APS models is validated under typical working scenarios, and the simulation results show that the control strategy has no high requirement on the communication speed between central controller and distributed controllers.

Modelling and understanding variability in wind generation will be increasingly important in the future with growing shares of wind power in energy systems. Crucially, the modelling needs to be extended to future scenarios, also considering the expected technological development of installations. Reanalysis data is often used in large-scale simulations to model the variability in wind. Wind power plant (WPP) data is also required, but may be only partially available. In this paper, a methodology for estimating missing hub height data is presented, using multiple regression models and large WPP and turbine datasets. The resulting estimated hub heights are presented on a pan-European level, and a scenario with capacity factor development until 2050 for two example countries is shown in detail.

One of the main challenges of the wind industry is the accurate prediction of the revenues that a developing project is expected to produce during its operation lifetime. The European Commission's Guidelines on State Aid for Environment Protection and Energy 2014-2020 (2014/C 200/01) (European Commission, 2014), enforced the transition from the Feed-in Tarif (FiT) scheme to a market-oriented Feed-in Premium remuneration mechanism. This evolution creates additional uncertainty when evaluating the revenues of a wind energy project, since the remuneration of the produced energy is now market depended instead of stable, as it was under the FiT scheme. The present study attempts to estimate the level of uncertainty that the change of support scheme creates. The expected revenues under both schemes are calculated for three (3) continuous years in the Greek market with the assumption that the strike price of the new FiP scheme coincides with the fixed tariff of the FiT scheme and the results are compared in an annual and total period. The study takes into account the revenues from the day-ahead market (i.e. the only wholesale market currently exists in Greece) and from the support mechanism. The results of the comparison reveal small fluctuation in the annual revenues of the wind stations examined between the two schemes, which does not seem to increase when examining the total 3-year period

Wind turbine power curve upgrades have recently been attracting considerable investment in the operation of wind farms and noticeable attention in the wind energy literature. Due to the non-stationary conditions to which wind turbines are subjected, the most consistent strategy for quantifying the production improvement from the installation of an upgrade is comparing, after at least some months of operation, the post-upgrade production against a model of the pre-upgrade production under the same conditions. Formulating adequate models for the power of the upgraded wind turbines is in general non-trivial and it can be difficult to achieve the precision that wind turbine practitioners typically require for the production assessment. In the present work, a multivariate linear method for selecting the most appropriate input for modeling a given output is presented and applied to a test case. The test case is a multi-megawatt wind turbine owned by Renvico, on whose blades vortex generators and passive flow control devices have been installed. Applying the proposed method, it is possible to compute with precision the production improvement in the first five months of post-upgrade operation (purely aerodynamic upgrade) and in the subsequent three months (aerodynamic and control upgrade). It is therefore possible to appreciate the different contributions to the production enhancement from the aerodynamic and control improvement. A non-upgraded wind turbine from the same wind farm is also studied and the precision of the results inspires the use of the proposed method for performance control and monitoring in general.

Several studies have used the power curve as a critical indicator to assess the performance of wind turbines. However, the wind turbine internal operation is affected by various parameters, particularly by blade pitch angle. Continuous monitoring of blade pitch angle can be useful for power performance assessment of wind turbines. The blade pitch curve describes the nonlinear relationship between pitch angle and hub height wind speed which to date has been little explored for wind turbine condition monitoring. Gaussian Process models are nonlinear and nonparametric technique, based on Bayesian probability theory. Such models have the potential give results quickly and efficiently. In this paper, we propose a Gaussian Process model to predict blade pitch curve of a wind turbine for condition monitoring purposes. The obtained Gaussian Process based blade pitch curve is then compared with a conventional approach based on a binned blade pitch curve for identifying operational anomalies purposes. Finally, the weaknesses and strengths of these methods are summarised. SCADA data from healthy wind turbines are used to train and evaluate the performance of these techniques.

Distributed temperature sensing (DTS) has been deployed for a field trial on a high voltage direct current (HVDC) cable in the North Sea. Temperature measurements using a fibre optic sensing cable bundled onto the HVDC cables are compared with both the cable characteristics and the cable route demonstrating an excellent agreement. Horizontal Directional Drilling (HDD), land and offshore cable joints, transitions as well as hot spots and excess burial are clearly visible. Thermal data thus helps in assessing the cable condition.

To date, the focus of the research on offshore wind turbines (WTs) has been mainly on how to minimise their capital cost, but Operation and Maintenance (O&M) can represent up to a third of the lifetime costs of an offshore wind farm. The cost for the assets repair/replacement and for the logistics of the maintenance operations are two of the biggest contributors to O&M expenses. While the first is going to rise with the employment of bigger structures, the latter can significantly increase dependently on the reliability of the components, and thus the necessity to performed unscheduled maintenance operations. Using the reliability data for a population of offshore WTs (representing the configurations most employed offshore), first, the share of the components failures to the O&M cost, together with an estimation of their dependency on some O&M parameters has been derived. Then, by following a cost-based Failure Modes Effects and Criticality Analysis (FMECA), and ranking the components through O&M cost priority number, the most critical components for O&M unplanned operations are identified.

The detection of abnormal operation modes is of fundamental importance for both operational management and predictive maintenance of wind turbines. Anomaly detection approaches in this context should consider the additional information content that probabilistic models can provide. Instead of binary anomaly classification, the probabilistic information is necessary for proper decision making and risk assessment. Common models, such as quantile and distribution regression can provide probabilistic information. While they are appropriate in predicting the cumulative distribution function, they struggle to accurately describe the probability of an event to occur. In this article we present a new, multi-task learning based approach for a continuous distribution regression with deep neural networks. Using real-world data from an offshore wind turbine, we show that with this model we can better reflect the probability of observed events than with conventional methods. While the predicted cumulative distribution function has a similar quality and no significant differences are visible in the continuous ranked probability score, the probability density function will be substantially smoother. This is also reflected in a significantly lower ignorance score.

Synchronous reluctance generators with ferrite magnets in the rotor (PMSynRG) are a good alternative to synchronous generators (SG) with rare-earth magnets. The comparison between a SG with rare-earth magnets and a PMSynRG with ferrite magnets of the same diameter, stack length, power and speed is given in the paper. Twice as less magnets are required for the PMSynRG with ferrite magnets than for the SG with rare-earth magnets. The cost of the ferrite magnets is 4.4 times less than of the rare earth magnets. Also, the PMSynRG with ferrite magnets has much higher efficiency than the SG. The half-integer slot number per pole and phase is chosen to achieve rather low torque ripple without skewing the rotor.