Life cycle assessment of the offshore wind farm alpha ventus

Due to better wind conditions at sea, offshore wind farms have the advantage of higher electricity production compared to onshore and inland wind farms. In contrast, a greater material input, leading to increased energy consumptions and emissions during the production phase, is required to build offshore wind farms. These contrary effects are investigated for the first German offshore wind farm alpha ventus in the North Sea. In a life cycle assessment its environmental influence is compared to that of Germany’s electricity mix.In comparison to the mix, alpha ventus had better indicators in nearly every investigated impact category. One kilowatt-hour electricity, generated by the wind farm, was burdened with 0.137 kWh Primary Energy-Equivalent and 32 g CO₂-Equivalent, which represented only a small proportion of the accordant values for the mix. Furthermore, the offshore foundations as well as the submarine cable were the main energy intensive components. The energetic and greenhouse gas payback period was less than one year.Therefore, offshore wind power, even in deep water, is compatible with the switch to sustainable electricity production relying on renewable energies. Additional research, taking backup power plants as well as increasingly required energy storage systems into account, will allow further calculation.     

A framework for data integration of offshore wind farms

Operation and maintenance play an important role in maximizing the yield and minimizing the downtime of wind turbines, especially offshore wind farms where access can be difficult due to harsh weather conditions for long periods. It contributes up to 25–30% to the cost of energy generation. Improved operation and maintenance (O&M) practices are likely to reduce the cost of wind energy and increase safety. In order to optimize the O&M, the importance of data exchange and knowledge sharing within the offshore wind industry must be realized. With more data available, it is possible to make better decisions, and thereby improve the recovery rates and reduce the operational costs. This article describes the development of a framework for data integration to optimize the remote operations of offshore wind farms.     

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.     

GHG emissions and energy performance of offshore wind power

This paper presents specific life cycle GHG emissions from wind power generation from six different 5 MW offshore wind turbine conceptual designs. In addition, the energy performance, expressed by the energy indicators Energy Payback Ratio (EPR) Energy Payback Time (EPT), is calculated for each of the concepts.There are currently few LCA studies in existence which analyse offshore wind turbines with rated power as great as 5 MW. The results, therefore, give valuable additional environmental information concerning large offshore wind power. The resulting GHG emissions vary between 18 and 31.4 g CO₂-equivalents per kWh while the energy performance, assessed as EPR and EPT, varies between 7.5 and 12.9, and 1.6 and 2.7 years, respectively. The relatively large ranges in GHG emissions and energy performance are chiefly the result of the differing steel masses required for the analysed platforms. One major conclusion from this study is that specific platform/foundation steel masses are important for the overall GHG emissions relating to offshore wind power. Other parameters of importance when comparing the environmental performance of offshore wind concepts are the lifetime of the turbines, wind conditions, distance to shore, and installation and decommissioning activities.Even though the GHG emissions from wind power vary to a relatively large degree, wind power can fully compete with other low GHG emission electricity technologies, such as nuclear, photovoltaic and hydro power.     

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.     

A comparison of methods for assessing power output in non‐uniform onshore wind farms

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshore farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non‐uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. We show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.     

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.     

Offshore wind energy in the world context

The interest for the exploitation of the offshore wind energy is growing in Europe, where man land use is very high resulting in strong limitation to the installation of onshore wind farms. The today offshore operating wind power is 12 MW, with two wind farms in Denmark and one in Netherlands; it starts to be significant (0.6%) in terms of the onshore power, 2000 MW in Europe.In the world the onshore installed wind power is exceeding 4000 MW, but not so much up to now has been done on the offshore area outside Europe.The European four years experience on the prototypical offshore wind farms looks significantly promising and suggests to promote a similar approach in many densely populated coastal countries in the world with high electricity demand.Results of studies are presented on the offshore wind potential in the European countries and of the tentative evaluation for the Mediterranean basin, and the seas of USA and China. A review is made of the offshore applications, particularly for the Nothern European seas.Economy and environmental trends are illustrated in parallel to those of maturing offshore technology. It is suggested to prepare an action plan to promote the development of the offshore applications in the world context.     

Valuing the manufacturing externalities of wind energy: assessing the environmental profit and loss of wind turbines in Northern Europe

This study draws from a concept from green accounting, lifecycle assessment, and industrial ecology known as 'environmental profit and loss” (EP&L) to determine the extent of externalities across the manufacturing lifecycle of wind energy. So far, no EP&Ls have involved energy companies and none have involved wind energy or wind turbines. We perform an EP&L for three types of wind turbines sited and built in Northern Europe (Denmark and Norway) by a major manufacturer: a 3.2 MW onshore turbine with a mixed concrete steel foundation, a 3.0 MW offshore turbine with a steel foundation, and a 3.0 MW offshore turbine with a concrete foundation. For each of these three turbine types, we identify and monetize externalities related to carbon dioxide emissions, air pollution, and waste. We find that total environmental losses range from €1.1 million for the offshore turbine with concrete foundation to €740,000 for onshore turbines and about €500,000 for an offshore turbine with steel foundation—equivalent to almost one‐fifth of construction cost in some instances. We conclude that carbon dioxide emissions dominate the amount of environmental damages and that turbines need to work for 2.5 to 5.5 years to payback their carbon debts. Even though turbines are installed in Europe, China and South Korea accounted for about 80% of damages across each type of turbine. Lastly, two components, foundations and towers, account for about 90% of all damages. We conclude with six implications for wind energy analysts, suppliers, manufacturers, and planners. Copyright © 2015 John Wiley & Sons, Ltd.     

Life cycle assessment of a wind farm and related externalities

This paper concentrates on the assessment of energy and emissions related to the production and manufacture of materials for an offshore wind farm as well as a wind farm on land based on a life cycle analysis (LCA) model. In Denmark a model has been developed for life cycle assessments of different materials. The model is able to assess the energy use related to the production, transportation and manufacture of 1 kg of material. The energy use is divided into fuels used in order to estimate the emissions through the life cycle. In the paper the model and the attached assumptions are described, and the model is demonstrated for two wind farms. The externalities for the wind farms are reported, showing the importance of life cycle assessment for renewable energy technologies.     

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.     

Life cycle assessment of a floating offshore wind turbine

A development in wind energy technology towards higher nominal power of the wind turbines is related to the shift of the turbines to better wind conditions. After the shift from onshore to offshore areas, there has been an effort to move further from the sea coast to the deep water areas, which requires floating windmills. Such a concept brings additional environmental impact through higher material demand. To evaluate additional environmental burdens and to find out whether they can be rebalanced or even offset by better wind conditions, a prospective life cycle assessment (LCA) study of one floating concept has been performed and the results are presented in this paper. A comparison with existing LCA studies of conventional offshore wind power and electricity from a natural gas combined cycle is presented. The results indicate similar environmental impacts of electricity production using floating wind power plants as using non-floating offshore wind power plants. The most important stage in the life cycle of the wind power plants is the production of materials. Credits that are connected to recycling these materials at the end-of-life of the power plant are substantial.     

Assessing the life cycle environmental impacts of wind power: A review of present knowledge and research needs

We critically review present knowledge of the life cycle environmental impacts of wind power. We find that the current body of life cycle assessments (LCA) of wind power provides a fairly good overall understanding of fossil energy use and associated pollution; our survey of results that appear in existing literature give mean values (± standard deviation) of, e.g., 0.060 (±0.058) kW h energy used and 19 (±13) g CO₂e emitted per kW h electricity, suggesting good environmental performance vis-à-vis fossil-based power. Total emissions of onshore and offshore wind farms are comparable. The bulk of emissions generally occur in the production of components; onshore, the wind turbine dominates, while offshore, the substructure becomes relatively more important. Strong positive effects of scale are present in the lower end of the turbine size spectrum, but there is no clear evidence for such effects for MW-sized units. We identify weaknesses and gaps in knowledge that future research may address. This includes poorly understood impacts in categories of toxicity and resource depletion, lack of empirical basis for assumptions about replacement of parts, and apparent lack of detailed considerations of offshore operations for wind farms in ocean waters. We argue that applications of the avoided burden method to model recycling benefits generally lack transparency and may be inconsistent. Assumed capacity factor values are generally higher than current mean realized values. Finally, we discuss the need for LCA research to move beyond unit-based assessments in order to address temporal aspects and the scale of impacts.     

A macro-level decision analysis of wind power as a solution for sustainable energy in the USA

This study aims to quantify the socio-economic and environmental impacts of producing electricity by wind power plants for the US electricity mix. To accomplish this goal, all direct and supply chain-related impacts of different onshore and offshore wind turbines are quantified using a hybrid economic input-output-based triple bottom line (TBL) life cycle assessment model. Furthermore, considering TBL sustainability implications of each onshore and offshore wind energy technology, a multi-criteria decision-making tool which is coupled with Monte Carlo simulation is utilised to find the optimal choice of onshore and offshore wind energy. The analysis results indicate that V90-3.0 MW wind turbines have lower impacts than V80-3.0 MW for both socio-economic and environmental indicators. The Monte Carlo simulation results reveal that when environmental issues are more important than socio-economic impacts, V90-3.0 MW offshore is selected among the alternatives.     

A Metric Space with LCOE Isolines for Research Guidance in wind and hydrokinetic energy systems

This paper introduces a new Metric Space to guide the design of advanced wind energy systems and hydrokinetic energy converters such as tidal, ocean current and riverine turbines. The Metric Space can analyse farms that combine different or identical turbines and stand‐alone turbines. The first metric (M1) of the space considers the efficiency of the turbines in the farm, which is also proportional to the specific power per swept area at a given wind/water velocity (W/m²). The second metric (M2) describes the specific rotor area per unit of mass of the turbines (m²/kg). Both metrics depend on the primary design characteristics of the turbines, such as swept area, system size and mass, materials and efficiency, and are independent at first from external characteristics, such as atmospheric and ocean site conditions, cost of materials and economic factors. Combining both metrics, and for a given set of external characteristics, the resulting Metric Space M2/M1 displays the Levelized Cost of Energy (LCOE) standards as isolines. This graphical representation provides a quick understanding of the cost and state of the technology. It also offers a practical guidance to choose the research tasks and strategy to design advanced wind and hydrokinetic energy systems. The paper applies the new Metric Space to several case studies, including large and small onshore wind turbines, floating and bottom‐fixed offshore wind turbines, downwind rotors, multi‐rotor and hybrid systems, airborne wind energy systems, wind farms and tidal energy converters.     

Coordinate control strategy for stability operation of offshore wind farm integrated with Diode-rectifier HVDC

Due to low investment cost and high reliability, a new scheme called DR-HVDC (Diode Rectifier based HVDC) transmission was recently proposed for grid integration of large offshore wind farms. However, in this scheme, the application of conventional control strategies for stability operation face several challenges due to the uncontrollability of the DR. In this paper, a coordinated control strategy of offshore wind farms using the DR-HVDC transmission technology to connect with the onshore grid, is investigated. A novel coordinated control strategy for DR-HVDC is proposed based on the analysis of the DC current control ability of the full-bridge-based modular multilevel converter (FB-MMC) at the onshore station and the input and output characteristics of the diode rectifier at the offshore. Considering the characteristics of operation stability and decoupling between reactive power and active power, a simplified design based on double-loop droop control for offshore AC voltage is proposed after power flow and voltage–current (I–V) characteristics of the offshore wind farm being analyzed. Furthermore, the impact of onshore AC fault to offshore wind farm is analyzed, and a fast fault detection and protection strategy without relying on communication is proposed. Case studies carried out by PSCAD/EMTDC verify the effectiveness of the proposed control strategy for the start up, power fluctuation, and onshore and offshore fault conditions.     

Offshore wind farm site selection study around Jeju Island,South Korea

This study suggests strategies for conducting an offshore wind farm site selection and evaluates feasible offshore wind farm sites in the coastal areas of Jeju Island, South Korea. The site selection criteria are classified into four categories: energy resources and economics, conservation areas and landscape protection, human activities, and the marine environment and marine ecology. We used marine spatial techniques from GIS and the investigated resources available in the country. The results indicate that offshore wind farms can be located along a wide range of the eastern and western coasts of Jeju Island, considering energy resources and economics only. However, when considering the four categories presented in this study, the number of feasible offshore wind farm sites was significantly less than when only energy resources and economics were considered. The data and analysis presented in this study will be useful for the offshore wind farm site selection around Jeju Island, and it will also contribute to minimizing the environmental impacts and reducing the social conflicts between stakeholders.     

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.     

The impact of land use constraints in multi-objective energy-noise wind farm layout optimization

Recently the environmental impact of onshore wind farms is receiving major attention from both governments and wind farm designers. As land is more extensively exploited for wind farms, it is more likely for wind turbines to be in proximity with human dwellings, infrastructure (e.g. roads, transmission lines), and natural habitats (e.g. rivers, lakes, forests). This proximity makes significant portions of land unusable for the designers, introducing a set of land-use constraints. In this study, we conduct a constrained and continuous-variable multi-objective optimization that considers energy and noise as its objective functions, based on Jensen's wake model and the ISO-9613-2 noise standard. A stochastic evolutionary algorithm (NSGA-II) solves the optimization problem, while the land-use constraints are handled with static and dynamic penalty functions. Results of this study illustrate the effect of constraint severity and spatial distribution of unusable land on the trade-off between energy generation and noise production.     

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.