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

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

Towards quantification of condition monitoring benefit for wind turbine generators

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

O&M Models for Ocean Energy Converters: Calibrating through Real Sea Data

Of the cost centres that combine to result in Levelised Cost of Energy (LCOE), O&M costs play a significant part. Several developers have calculated component costs, demonstrating how they can become commercially competitive with other forms of renewable energy. However, there are uncertainties relating to the O&M figures that can only be reduced through lessons learned at sea. This work presents an O&M model calibrated with data from real sea experience of a wave energy device deployed at the Biscay Marine energy Platform (BiMEP): the OPERA O&M Model. Two additional case studies, utilising two other O&M calculation methodologies, are presented for comparison with the OPERA O&M Model. The second case study assumes the inexistence of an O&M model, utilising a Simplified Approach. The third case study applies DTOcean’s (a design tool for ocean energy arrays) O&M module. The results illustrate the potential advantages of utilising real sea data for the calibration and development of an O&M model. The Simplified Approach was observed to overestimate LCOE when compared to the OPERA O&M Model. This work also shows that O&M models can be used for the definition of optimal maintenance plans to assist with OPEX reduction.The authors are grateful to the European commission for funding the OPERA and EnFAIT projects as part of the Horizon 2020 framework. The authors also thankful to Oceantec-Idom for providing feedback to OPERA model’s inputs. A special thanks to Shona Pennock and Donald Noble for their diligent proofreading of this paper

[Report of] Specialist Committee V.4: ocean, wind and wave energy utilization

The committee's mandate was :Concern for structural design of ocean energy utilization devices, such as offshore wind turbines, support structures and fixed or floating wave and tidal energy converters. Attention shall be given to the interaction between the load and the structural response and shall include due consideration of the stochastic nature of the waves, current and wind

Does Telemedical Support of First Responders Improve Guideline Adherence in an Offshore Emergency Scenario? A Simulator-Based Prospective Study

OBJECTIVE: To investigate, in a simulator-based prospective study, whether telemedical support improves quality of emergency first response (performance) by medical non-professionals to being non-inferior to medical professionals. SETTING: In a simulated offshore wind power plant, duos (teams) of offshore engineers and teams of paramedics conducted the primary survey of a simulated patient. PARTICIPANTS: 38 offshore engineers and 34 paramedics were recruited by the general email invitation. INTERVENTION: Teams (randomised by lot) were supported by transmission technology and a remote emergency physician in Berlin. OUTCOME MEASURES: From video recordings, performance (17 item checklist) and required time (up to 15 min) were quantified by expert rating for analysis. Differences were analysed using two-sided exact Mann-Whitney U tests for independent measures, non-inferiority was analysed using Schuirmann one-sided test. The significance level of 5 % was Holm-Bonferroni adjusted in each family of pairwise comparisons. RESULTS: Nine teams of engineers with, nine without, nine teams of paramedics with and eight without support completed the task. Two experts quantified endpoints, insights into rater dependence were gained. Supported engineers outperformed unsupported engineers (p<0.01), insufficient evidence was found for paramedics (p=0.11). Without support, paramedics outperformed engineers (p<0.01). Supported engineers' performance was non-inferior (at one item margin) to that by unsupported paramedics (p=0.03). Supported groups were slower than unsupported groups (p<0.01). CONCLUSIONS: First response to medical emergencies in offshore wind farms with substantially delayed professional care may be improved by telemedical support. Future work should test our result during additional scenarios and explore interdisciplinary and ecosystem aspects of this support. TRIAL REGISTRATION NUMBER: DRKS0001437

Modelling offshore wind farm operation and maintenance with view to estimating the benefits of condition monitoring

Offshore wind energy is progressing rapidly and playing an increasingly important role in electricity generation. Since the Kyoto Protocol in February 2005, Europe has been substantially increasing its installed wind capacity. Compared to onshore wind, offshore wind allows the installation of larger turbines, more extensive sites, and encounters higher wind speed with lower turbulence. On the other hand, harsh marine conditions and the limited access to the turbines are expected to increase the cost of operation and maintenance (O&M costs presently make up approximately 20-25% of the levelised total lifetime cost of a wind turbine). Efficient condition monitoring has the potential to reduce O&M costs. In the analysis of the cost effectiveness of condition monitoring, cost and operational data are crucial. Regrettably, wind farm operational data are generally kept confidential by manufacturers and wind farm operators, especially for the offshore ones.To facilitate progress, this thesis has investigated accessible SCADA and failure data from a large onshore wind farm and created a series of indirect analysis methods to overcome the data shortage including an onshore/offshore failure rate translator and a series of methods to distinguish yawing errors from wind turbine nacelle direction sensor errors. Wind turbine component reliability has been investigated by using this innovative component failure rate translation from onshore to offshore, and applies the translation technique to Failure Mode and Effect Analysis for offshore wind. An existing O&M cost model has been further developed and then compared to other available cost models. It is demonstrated that the improvements made to the model (including the data translation approach) have improved the applicability and reliability of the model. The extended cost model (called StraPCost+) has been used to establish a relationship between the effectiveness of reactive and condition-based maintenance strategies. The benchmarked cost model has then been applied to assess the O&M cost effectiveness for three offshore wind farms at different operational phases.Apart from the innovative methodologies developed, this thesis also provides detailed background and understanding of the state of the art for offshore wind technology, condition monitoring technology. The methodology of cost model developed in this thesis is presented in detail and compared with other cost models in both commercial and research domains.Offshore wind energy is progressing rapidly and playing an increasingly important role in electricity generation. Since the Kyoto Protocol in February 2005, Europe has been substantially increasing its installed wind capacity. Compared to onshore wind, offshore wind allows the installation of larger turbines, more extensive sites, and encounters higher wind speed with lower turbulence. On the other hand, harsh marine conditions and the limited access to the turbines are expected to increase the cost of operation and maintenance (O&M costs presently make up approximately 20-25% of the levelised total lifetime cost of a wind turbine). Efficient condition monitoring has the potential to reduce O&M costs. In the analysis of the cost effectiveness of condition monitoring, cost and operational data are crucial. Regrettably, wind farm operational data are generally kept confidential by manufacturers and wind farm operators, especially for the offshore ones.To facilitate progress, this thesis has investigated accessible SCADA and failure data from a large onshore wind farm and created a series of indirect analysis methods to overcome the data shortage including an onshore/offshore failure rate translator and a series of methods to distinguish yawing errors from wind turbine nacelle direction sensor errors. Wind turbine component reliability has been investigated by using this innovative component failure rate translation from onshore to offshore, and applies the translation technique to Failure Mode and Effect Analysis for offshore wind. An existing O&M cost model has been further developed and then compared to other available cost models. It is demonstrated that the improvements made to the model (including the data translation approach) have improved the applicability and reliability of the model. The extended cost model (called StraPCost+) has been used to establish a relationship between the effectiveness of reactive and condition-based maintenance strategies. The benchmarked cost model has then been applied to assess the O&M cost effectiveness for three offshore wind farms at different operational phases.Apart from the innovative methodologies developed, this thesis also provides detailed background and understanding of the state of the art for offshore wind technology, condition monitoring technology. The methodology of cost model developed in this thesis is presented in detail and compared with other cost models in both commercial and research domains

State of the Art in the Optimisation of Wind Turbine Performance Using CFD

Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained

Control of multi-terminal HVDC networks towards wind power integration: A review

© 2015 Elsevier Ltd. More interconnections among countries and synchronous areas are foreseen in order to fulfil the EU 2050 target on the renewable generation share. One proposal to accomplish this challenging objective is the development of the so-called European SuperGrid. Multi-terminal HVDC networks are emerging as the most promising technologies to develop such a concept. Moreover, multi-terminal HVDC grids are based on highly controllable devices, which may allow not only transmitting power, but also supporting the AC grids to ensure a secure and stable operation. This paper aims to present an overview of different control schemes for multi-terminal HVDC grids, including the control of the power converters and the controls for power sharing and the provision of ancillary services. This paper also analyses the proposed modifications of the existing control schemes to manage high participation shares of wind power generation in multi-terminal grids.Postprint (author's final draft

On modelling insights for emerging engineering problems : a case study on the impact of climate uncertainty on the operational performance of offshore wind farms

This paper considers the technical and practical challenges involved in modelling emerging engineering problems. The inherent uncertainty and potential for change in operating environment and procedures adds significant complexity to the model development process. This is demonstrated by considering the development of a model to quantify the uncertainty associated with the influence of the wind and wave climate on the energy output of offshore wind farms which may result in sub-optimal operating decisions and site selection due to the competing influence of wind speed on power production and wave conditions on availability. The financial profitability of current and future projects may be threatened if climate uncertainty is not included in the planning and operational decision making process. A comprehensive climate and wind farm operational model was developed using a time series Monte Carlo simulation to model the performance of offshore wind farms, identifying non-linear relationships between climate, availability, energy output and capacity factor. This model was evaluated by engineers planning upcoming offshore wind farms to determine its usefulness for supporting operational decision making. From this, new consideration was given to the challenges in developing and applying complex simulations for emerging engineering problems

Cost and losses associated with offshore wind farm collection networks which centralise the turbine power electronic converters

Costs and losses have been calculated for several different network topologies, which centralise the turbine power electronic converters, in order to improve access for maintenance. These are divided into star topologies, where each turbine is connected individually to its own converter on a platform housing many converters, and cluster topologies, where multiple turbines are connected through a single large converter. Both AC and DC topologies were considered, along with standard string topologies for comparison. Star and cluster topologies were both found to have higher costs and losses than the string topology. In the case of the star topology, this is due to the longer cable length and higher component count. In the case of the cluster topology, this is due to the reduced energy capture from controlling turbine speeds in clusters rather than individually. DC topologies were generally found to have a lower cost and loss than AC, but the fact that the converters are not commercially available makes this advantage less certain