Greenhouse gas emissions from electricity generated by offshore wind farms

For wind power generation offshore sites offer significantly better wind conditions compared to onshore. At the same time, the demand for raw materials and therefore the related environmental impacts increase due to technically more demanding wind energy converters and additional components (e.g. substructure) for the balance of plant. Additionally, due to environmental concerns offshore wind farms will be sited farshore (i.e. in deep water) in the future having a significant impact on the operation and maintenance efforts (O&M). Against this background the goal of this analysis is an assessment of the specific GHG (greenhouse gas) emissions as a function of the site conditions, the wind mill technology and the O&M necessities. Therefore, a representative offshore wind farm is defined and subjected to a detailed LCA (life cycle assessment). Based on parameter variations and modifications within the technical and logistical system, promising configurations regarding GHG emissions are determined for different site conditions. Results show, that all parameters related to the energy yield have a distinctive impact on the specific GHG emissions, whereas the distance to shore and the water depth affect the results marginally. By utilizing the given improvement potentials GHG emissions of electricity from offshore wind farms are comparable to those achieved onshore.     

Efficiency and effectiveness of wind farms—keys to cost optimized operation and maintenance

Operation and maintenance (O&M) cost will be the key to the economic viability of large offshore wind farms planned worldwide. In order to support investment decisions a systematic mathematical approach to the O&M cost contributions is required prior to detailed engineering or even construction of the wind farm.Adopting the general terms of efficiency, productivity and effectiveness defined for production processes we introduce the Wind Farm Process and its Total Overall Equipment Effectiveness (TotalOEE) by considering wind farms performing a transformation of produced electrical energy to delivered (sold) electrical energy. This transformation process consists of an installation, i.e. properly selected wind energy converters and their arrangement to form a wind farm, and of a process comprising operation and maintenance. Both are the subject of optimization to maximize the annual energy output by minimizing the different kinds of losses.In a systematic approach to the causes and nature of losses in wind farms the terms theoretical production time, available production time and valuable production time are redefined in unit full load hours. Then, a calculation scheme is developed to quantify wind farm production losses in terms of planned or unplanned downtimes and speed losses and to relate the associated reduction of revenues ΔR to the theoretical maximum of annual wind park revenues R_theo(park). It leads to the simple equation ΔR/R_theo = TotalOEE – 1 < 0.     

Offshore wind turbine fault alarm prediction

Offshore wind operations and maintenance (O&M) costs could reach up to one third of the overall project costs. In order to accelerate the deployment of offshore wind farms, costs need to come down. A key contributor to the O&M costs is the component failures and the downtime caused by them. Thus, an understanding is needed on the root cause of these failures. Previous research has indicated the relationship between wind turbine failures and environmental conditions. These studies are using work‐order data from onshore and offshore assets. A limitation of using work orders is that the time of the failure is not known and consequently, the exact environmental conditions cannot be identified. However, if turbine alarms are used to make this correlation, more accurate results can be derived. This paper quantifies this relationship and proposes a novel tool for predicting wind turbine fault alarms for a range of subassemblies, using wind speed statistics. A large variation of the failures between the different subassemblies against the wind speed are shown. The tool uses 5 years of operational data from an offshore wind farm to create a data‐driven predictive model. It is tested under low and high wind conditions, showing very promising results of more than 86% accuracy on seven different scenarios. This study is of interest to wind farm operators seeking to utilize the operational data of their assets to predict future faults, which will allow them to better plan their maintenance activities and have a more efficient spare part management system.     

Failure rate,repair time and unscheduled O&M cost analysis of offshore wind turbines

Determining and understanding offshore wind turbine failure rates and resource requirement for repair are vital for modelling and reducing O&M costs and in turn reducing the cost of energy. While few offshore failure rates have been published in the past even less details on resource requirement for repair exist in the public domain. Based on ~350 offshore wind turbines throughout Europe this paper provides failure rates for the overall wind turbine and its sub‐assemblies. It also provides failure rates by year of operation, cost category and failure modes for the components/sub‐assemblies that are the highest contributor to the overall failure rate. Repair times, average repair costs and average number of technicians required for repair are also detailed in this paper. An onshore to offshore failure rate comparison is carried out for generators and converters based on this analysis and an analysis carried out in a past publication. The results of this paper will contribute to offshore wind O&M cost and resource modelling and aid in better decision making for O&M planners and managers. Copyright © 2015 John Wiley & Sons, Ltd.     

Cost-benefit assessment framework for robotics-driven inspection of floating offshore wind farms

Operations and maintenance (O&M) of floating offshore wind farms (FOWFs) poses various challenges in terms of greater distances from the shore, harsher weather conditions, and restricted mobility options. Robotic systems have the potential to automate some parts of the O&M leading to continuous feature-rich data acquisition, operational efficiency, along with health and safety improvements. There remains a gap in assessing the techno-economic feasibility of robotics in the FOWF sector. This paper investigates the costs and benefits of incorporating robotics into the O&M of a FOWF. A bottom-up cost model is used to estimate the costs for a proposed multi-robot platform (MRP). The MRP houses unmanned aerial vehicle (UAV) and remotely operated vehicle (ROV) to conduct the inspection of specific FOWF components. Emphasis is laid on the most conducive O&M activities for robotization and the associated technical and cost aspects. The simulation is conducted in Windfarm Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT), where the metrics of incurred operational expenditure (OPEX) and the inspection time are calculated and compared with those of a baseline case consisting of crew transfer vessels, rope-access technicians, and divers. Results show that the MRP can reduce the inspection time incurred, but this reduction has dependency on the efficacy of the robotic system and the associated parameterization e.g., cost elements and the inspection rates. Conversely, the increased MRP day rate results in a higher annualized OPEX. Residual risk is calculated to assess the net benefit of incorporating the MRP. Furthermore, sensitivity analysis is conducted to find the key parameters influencing the OPEX and the inspection time variation. A key output of this work is a robust and realistic framework which can be used for the cost-benefit assessment of future MRP systems for specific FOWF activities.     

Towards a mature offshore wind energy technology—guidelines from the opti‐OWECS project

The article reviews the main results of the recent European research project Opti‐OWECS (‘Structural and Economic Optimisation of Bottom‐Mounted Offshore Wind Energy Converters'), which has significantly improved the understanding of the requirements for a large‐scale utilization of offshore wind energy. An integrated design approach was demonstrated for a 300 MW offshore wind farm at a demanding North Sea site. Several viable solutions were obtained and one was elaborated to include the design of all major components. Simultaneous structural and economic optimization took place during the different design stages. An offshore wind energy converter founded on a soft–soft monopile was tailored with respect to the distinct characteristics of dynamic wind and wave loading. The operation and maintenance behaviour of the wind farm was analysed by Monte Carlo simulations. With an optimized maintenance strategy and suitable hardware a high availability was achieved. Based upon the experience from the structural design, cost models for offshore wind farms were developed and linked to a European database of the offshore wind energy potential. This enabled the first consistent estimate of cost of offshore wind energy for entire European regions. Copyright © 1999 John Wiley & Sons, Ltd.     

Minimising costs of wind: Risk control and operation & maintenance strategies

Wind energy is one of the most attractive sources of renewable energy (one reason being it is one of the most proven of all sustainable energy technologies, second only to hydropower). It is not surprising, therefore, that the number of on and offshore wind farms is rising. Technology risk for new and unproven turbines, ground and/or sea conditions and inclement weather are still important considerations. Peter Cassidy and Lisa Scott, Masons, UK provide a lawyers' perspective on risk control and operation & maintenance strategies in onshore and offshore wind.     

Environmental and social footprint of offshore wind energy. Comparison with onshore counterpart

Offshore wind power comprises a relatively new challenge for the international wind industry with a demonstration history of around twenty years and a ten-year commercial history for large, utility-scale projects. By comparison to other forms of electric power generation, offshore wind energy is generally considered to have relatively benign effects on the marine environment. However, offshore projects include platforms, turbines, cables, substations, grids, interconnection and shipping, dredging and associated construction activity. The Operation & Maintenance (O&M) activities include the transport of employees by vessel or helicopter and occasional hardware retrofits. Therefore, various impacts are incurred in the construction, operation and decommissioning phases; mainly the underwater noise and the impacts on the fauna. Based on the fact that in many of the aforementioned issues there are still serious environmental uncertainties, contradictive views and emerging research, the present work intents to provide a thorough literature review on the environmental and social impacts of offshore wind energy projects in comparison with the onshore counterparts.     

The impact of wind resource spatial variability on floating offshore wind farms finance

Wind resource availability determines the financial performance of wind farms as it is directly related to production. Offshore wind developers require great investments to design, build, operate and dismantle offshore wind farms. Furthermore, the investments in the offshore floating wind sector are expected to increase in the future. Because of that, the assessment of the variability of the investments, mainly because of the wind resource variability, seems to be a crucial step in the design methodology. Consequently, a flexible methodology for supporting offshore floating wind farm optimal location assessment is presented in this paper. The proposed methodology is focused on including the offshore wind resource variability and its influence on the power production of floating wind farms, as well as on the main financial indicators (internal rate of return, net present value, pay‐back period and cost of energy). The methodology is applied to the north coast of Spain, and it allows to identify the most promising sites for offshore wind farms deployment. Differences on the cost of energy up to 100% can be found in the area under study. The methodology proposed has been conceived to be site‐independent and applied at any spatial and time horizon. Copyright © 2017 John Wiley & Sons, Ltd.     

The economics of wind energy

This article presents the outcomes of a recent study carried out among wind energy manufacturers and developers regarding the current generation costs of wind energy projects in Europe, the factors that most influence them, as well as the reasons behind their recent increase and their expected future evolution. The research finds that the generation costs of an onshore wind farm are between 4.5 and 8.7 €cent/kWh; 6–11.1 €cent/kWh when located offshore, with the number of full hours and the level of capital cost being the most influencing elements. Generation costs have increased by more than 20% over the last 3 years mainly due to a rise of the price of certain strategic raw materials at a time when the global demand has boomed. However, the competitive position of wind energy investments vis-à-vis other technologies has not been altered. In the long-term, one would expect production costs go down; whether this will be enough to offset the higher price of inputs will largely depend on the application of correct policies, like R&D in new materials, O&M with remote-control devices, offshore wind turbines and substructures; introduction of advanced siting and forecasting techniques; access to adequate funding; and long-term legal stability.     

海上风电机组塔架基础一体化设计

  [目的]  随着国家对于海上风电竞价上网指导意见的出台,降低开发成本的需求越来越迫切,急需通过技术创新降低成本。而海上塔架和基础的成本,显著影响着海上风电的平准化度电成本LCoE(Levelized Cost of Energy),直接决定着海上风电项目的竞争力。  [方法]  为了有效降低塔架基础的成本,文章提出了基于数字化云平台iDO(integrated Design Offshore)的一体化设计方法,对极端极限状态ULS工况下结构的静强度、疲劳极限状态FLS工况下结构的疲劳损伤进行了数值计算分析。为验证一体化设计方法在降低海上风电塔架基础成本的效果,文章针对两个实际工程项目,基于iDO云平台和传统分步迭代法SIA(Sequentially Iterated Approach)进行设计分析,对比ULS工况和FLS工况下的结构安全衡准指标。  [结果]  计算结果表明:ULS和FLS工况下,基于iDO云平台的一体化设计方法比SIA在结构强度、变形、疲劳损伤等指标有较大幅度下降,可显著优化塔架基础结构,降低结构重量,减小整个支撑结构成本,降低海上风电的LCoE。  [结论]  在实际海上风电工程项目应用中,基于iDO云平台的一体化设计方法可有效降低塔架基础结构成本,从而提高海上风电项目的竞争力,同时可对未来海上风电支撑结构优化设计提供借鉴。     

Fatigue distribution optimization for offshore wind farms using intelligent agent control

A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent agent is studied using topology models. The reference power of an individual wind turbine from the wind farm controller is re‐dispatched to balance the turbine fatigue in the power dispatch intervals. In the fatigue optimization, the goal function is to minimize the standard deviation of the fatigue coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent control approach is verified through the simulation of wind data from the Horns Rev offshore wind farm. The results illustrate that intelligent agent control is a feasible way to optimize fatigue distribution in wind farms, which may reduce the maintenance frequency and extend the service life of large‐scale wind farms. Copyright © 2012 John Wiley & Sons, Ltd.     

海上风电场智慧运维管理系统

[目的]针对海上风电场运维安全管理,提出了海上风电场智慧运维管理系统.[方法]通过海上风电智慧调度系统、海上风电雷达多源跟踪及边界警示系统、海上风电场风机平台作业监管系统,搭建出海上风电场智慧运维管理系统.[结果]通过陆上集控中心的海上风电智慧调度系统,实现人员的安全管理以及船舶调度.通过海上风电雷达多源跟踪及边界警示...     

Wind energy development and its environmental impact: A review

Wind energy, commonly recognized to be a clean and environmentally friendly renewable energy resource that can reduce our dependency on fossil fuels, has developed rapidly in recent years. Its mature technology and comparatively low cost make it promising as an important primary energy source in the future. However, there are potential environmental impacts due to the installation and operation of the wind turbines that cannot be ignored. This paper aims to provide an overview of world wind energy scenarios, the current status of wind turbine development, development trends of offshore wind farms, and the environmental and climatic impact of wind farms. The wake effect of wind turbines and modeling studies regarding this effect are also reviewed.     

Guidelines for assessment of investment cost for offshore wind generation

Offshore wind generation represents a key element for development of renewable energy, thanks to higher availability of energy source and lower presence of constraints. However, the feasibility of offshore wind farms has to be carefully evaluated, due to remarkable economical efforts required. In this paper, economic issues concerning costs in pre-investment and investment stages for offshore wind farms exploiting alternating-current transmission system are analysed. Single cost centres are detailed, taking into account technical features and current equipment exploitation. The aim is to formulate a general model to evaluate the total investment depending on wind farm layout. The model is employed to determine the most suitable connection solution for a 150-MW test wind farm, accounting for different connection schemes and the presence of an offshore or onshore substation. Further tests are run to evaluate cost variation for larger wind farms with different nominal voltage levels.     

Rapid sizing of a hydrogen-battery storage for an offshore wind farm using convex programming

This paper carries out a comprehensive analysis on an offshore wind farm equipped with a hybrid storage comprised of hydrogen and battery, from the perspective of economic effectiveness. To rapidly evaluate the system economy, a computationally efficient convex program that takes the nonlinear storage efficiencies into account is provided, which can simultaneously and synergistically optimize the storage sizing and energy management over a long offshore wind cycle. In the analysis, a case study on the optimal configuration and operation of the hybrid storage is thoroughly investigated, answering what the scalings are and how the storage functions in the offshore wind farm. Comparisons to other offshore wind farms with none or only one storage type further demonstrate the advantage of combining hydrogen plant and battery. Influences of the offshore wind electricity price of grid parity and hydrogen price on the system economies, in the terms of total annual cost, net annual profit and hydrogen production cost, are also discussed, revealing sensitivity and dependency of the scalings. Finally, this paper presents the future potential of applying hydrogen plant in the offshore wind farm, from the angles of hydrogen production cost and energy saving.     

ENDOW (efficient development of offshore wind farms): modelling wake and boundary layer interactions

While experience gained through the offshore wind energy projects currently operating is valuable, a major uncertainty in estimating power production lies in the prediction of the dynamic links between the atmosphere and wind turbines in offshore regimes. The objective of the ENDOW project was to evaluate, enhance and interface wake and boundary layer models for utilization offshore. The project resulted in a significant advance in the state of the art in both wake and marine boundary layer models, leading to improved prediction of wind speed and turbulence profiles within large offshore wind farms. Use of new databases from existing offshore wind farms and detailed wake profiles collected using sodar provided a unique opportunity to undertake the first comprehensive evaluation of wake models in the offshore environment. The results of wake model performance in different wind speed, stability and roughness conditions relative to observations provided criteria for their improvement. Mesoscale model simulations were used to evaluate the impact of thermal flows, roughness and topography on offshore wind speeds. The model hierarchy developed under ENDOW forms the basis of design tools for use by wind energy developers and turbine manufacturers to optimize power output from offshore wind farms through minimized wake effects and optimal grid connections. The design tools are being built onto existing regional‐scale models and wind farm design software which was developed with EU funding and is in use currently by wind energy developers. Copyright © 2004 John Wiley & Sons, Ltd.     

生态系统理念在海上风电项目管理中的应用研究

  [目的]  中国海上风电行业已迈入快速发展期,如何创新项目开发管理模式,有效应对海上风电造价高、界面多、工期长等问题,实现成本降低、效能提升,是推动海上风电行业健康快速发展的重要保障。  [方法]  通过将生态系统理念应用到海上风电场项目开发建设和运营管理中,探索构建海上风电场生态系统,以搭建风电场神经网络为核心,提高整体关联效能,实现最优开发目标;利用层次分析法对系统影响因子权重进行定量分析。  [结果]  通过海上风电场生态系统的构建,使海上风电场具备信息快速的收集、存储、共享、分析和反馈调节功能,降本增效,提升风电场稳定性。  [结论]  生态系统的引入为海上风电项目的开发管理和提供了新的思路,借助人工智能技术等前沿科技的发展,海上风电场生态系统也将不断完善和广泛应用。     

风电场的组合维修策略研究

为降低风电场维修成本,提出针对风电场的风电机组部件组合维修策略。在各部件故障率服从威布尔分布的基础上,确定各部件的最优预防性维修周期,进而确定各部件后续预防性维修的实施时刻。将未来一段时间内的全部维修任务按分组方案组合为多个维修组,单一维修组内包含的全部维修任务采用分层优化方法安排给多支维修队一起执行,以使在风电机组停机时间最短情况下维修队工作时间最短。对比组合维修策略与预防性维修策略的维系成本,以分组方案节约维修成本为适应度,使用遗传算法求解最优分组方案。仿真结果验证了该策略可有效减少风电机组的停机时间,降低风电场维修成本。     

Optimizing hybrid offshore wind farms for cost-competitive hydrogen production in Germany

Nearly 96% of the world's current hydrogen production comes from fossil-fuel-based sources, contributing to global greenhouse gas emissions. Hydrogen is often discussed as a critical lever in decarbonizing future power systems. Producing hydrogen using unsold offshore wind electricity may offer a low-carbon production pathway and emerging business model. This study investigates whether participating in an ancillary service market is cost competitive for offshore wind-based hydrogen production. It also determines the optimal size of a hydrogen electrolyser relative to an offshore wind farm. Two flexibility strategies for offshore wind farms are developed in this study: an optimal bidding strategy into ancillary service markets for offshore wind farms that build hydrogen production facilities and optimal sizing of Power-to-Hydrogen (PtH) facilities at wind farms. Using empirical European power market and wind generation data, the study finds that offshore-wind based hydrogen must participate in ancillary service markets to generate net positive revenues at current levels of wind generation to become cost competitive in Germany. The estimated carbon abatement cost of “green” hydrogen ranges between 187 EUR/tonCO₂e and 265 EUR/tonCO₂e. Allowing hydrogen producers to receive similar subsidies as offshore wind farms that produce only electricity could facilitate further cost reduction. Utilizing excess and intermittent offshore wind highlights one possible pathway that could achieve increasing returns on greenhouse gas emission reductions due to technological learning in hydrogen production, even under conditions where low power prices make offshore wind less competitive in the European electricity market.