Cost dynamics of wind power

This paper describes an analysis of the prospects of reducing the cost of wind-generated electricity. Special attention has been paid to the dynamic development of wind turbines, i.e. development based on experience gained in the production and use of wind turbines. Historical and future cost reductions associated with wind turbines are described using experience curves. The results of the analysis show that although the experience curve for wind turbines indicates relatively moderate cost reductions there is potential for considerable cost reductions in wind-generated electricity. This is due to the fact that the cost of wind-generated electricity will be affected by improved performance and reduced operating and maintenance costs, in addition to the reduction in cost of wind turbines. The results show that the average cost of wind-generated electricity will almost be reduced by half by the year 2020, assuming an annual market growth of 15–20%.     

The economics of visual disamenity reductions of offshore wind farms—Review and suggestions from an emerging field

The offshore wind power generation market is currently experiencing large growth rates on a global scale and investments exceeding several billion euro are being made. From a welfare economic point of view there is a non-trivial economic trade-off between offshore wind generation costs and the visual impacts from offshore wind farms. Offshore wind farms close to the shore generate cheaper electricity, but also cause higher levels of visual impacts compared to locations at larger distances. In the present paper we carry out a review of the stated preference studies that have elicited the demand for visual disamenity reduction from offshore wind farms. The review has three objectives: (a) to present the results of the different surveys; (b) to explore the more technical parts of the different surveys; and (c) to present the frontiers in the assessment of the demand for visual disamenity reductions associated with offshore wind farm locations. The paper is based on the results from five different studies. The review indicates that locations of offshore wind farms which are close to the shore generate significant welfare losses and that these can be reduced by locating the wind farms at more distant locations. The results also show that the welfare economic costs vary in terms of a range of socio demographic characteristics, experience with wind turbines and recreational activities. Finally, the review suggests that the welfare impacts related to the spatial distribution of the wind farms, intergenerational effects and experience with wind turbines are potential areas that would be beneficial to explore in future studies.     

Combining economic and fluid dynamic models to determine the optimal spacing in very large wind farms

Wind turbine spacing is an important design parameter for wind farms. Placing turbines too close together reduces their power extraction because of wake effects and increases maintenance costs because of unsteady loading. Conversely, placing them further apart increases land and cabling costs, as well as electrical resistance losses. The asymptotic limit of very large wind farms in which the flow conditions can be considered ‘fully developed’ provides a useful framework for studying general trends in optimal layouts as a function of dimensionless cost parameters. Earlier analytical work by Meyers and Meneveau (Wind Energy 15, 305–317 (2012)) revealed that in the limit of very large wind farms, the optimal turbine spacing accounting for the turbine and land costs is significantly larger than the value found in typical existing wind farms. Here, we generalize the analysis to include effects of cable and maintenance costs upon optimal wind turbine spacing in very large wind farms under various economic criteria. For marginally profitable wind farms, minimum cost and maximum profit turbine spacings coincide. Assuming linear‐based and area‐based costs that are representative of either offshore or onshore sites we obtain for very large wind farms spacings that tend to be appreciably greater than occurring in actual farms confirming earlier results but now including cabling costs. However, we show later that if wind farms are highly profitable then optimization of the profit per unit area leads to tighter optimal spacings than would be implied by cost minimization. In addition, we investigate the influence of the type of wind farm layout. © 2016 The Authors Wind Energy Published by John Wiley & Sons Ltd     

基于风电机组可靠性的风电场平准化成本模型研究

考虑综合风电场总体运行成本、风电机组可靠性及风电场发电量等多个维度,从风电场全生命周期视角出发,建立基于风电机组可靠性的风电场平准化成本模型,并通过算例分析得出,提升风电机组可靠性可降低风电机组的故障维护成本,提高风电场运行小时数,进而降低风电场平准化成本。在此基础上测算当前阶段风电实现平价上网需达到的利用小时数,最后给出促进风电发展的合理化建议。     

Technological learning in bioenergy systems

The main goal of this article is to determine whether cost reductions in different bioenergy systems can be quantified using the experience curve approach, and how specific issues (arising from the complexity of biomass energy systems) can be addressed. This is pursued by case studies on biofuelled combined heat and power (CHP) plants in Sweden, global development of fluidized bed boilers and Danish biogas plants. As secondary goal, the aim is to identify learning mechanisms behind technology development and cost reduction for the biomass energy systems investigated. The case studies reveal large difficulties to devise empirical experience curves for investment costs of biomass-fuelled power plants. To some extent, this is due to lack of (detailed) data. The main reason, however, are varying plant costs due to differences in scale, fuel type, plant layout, region etc. For fluidized bed boiler plants built on a global level, progress ratios (PRs) for the price of entire plants lies approximately between 90–93% (which is typical for large plant-like technologies). The costs for the boiler section alone was found to decline much faster. The experience curve approach delivers better results, when the production costs of the final energy carrier are analyzed. Electricity from biofuelled CHP-plants yields PRs of 91–92%, i.e. an 8–9% reduction of electricity production costs with each cumulative doubling of electricity production. The experience curve for biogas production displays a PR of 85% from 1984 to the beginning of 1990, and then levels to approximately 100% until 2002. For technologies developed on a local level (e.g. biogas plants), learning-by-using and learning-by-interacting are important learning mechanism, while for CHP plants utilizing fluidized bed boilers, upscaling is probably one of the main mechanisms behind cost reductions.     

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.     

Technological learning and cost reductions in wood fuel supply chains in Sweden

With its increasing use, the production costs of primary forest fuel (PFF) have declined over the last three decades in Sweden. The aims of this study are to quantify cost reductions of PFF production as achieved in Sweden over time, to identify underlying reasons for these reductions, and to determine whether the experience curve concept can be used to describe this cost reduction trend. If applicable, the suitability of this concept for future cost reduction analysis and for use in other countries is explored. The analysis was done using average national PFF price data (as a proxy for production costs), a number of production cost studies and data on annual Swedish production volumes. Results show that main cost reductions were achieved in forwarding and chipping of PFF, largely due to learning-by-doing, improved equipment and changes in organization. The price for wood fuel chips does follow an experience curve from 1975 to 2003 (over nine cumulative doublings). The progress ratio (PR) is calculated at 87%. However, given the uncertainty in data on PFF price and annual production volumes, the PR may range between 85% and 88%. It is concluded that in combination with the available supply potential of PFF and with bottom-up assessment of cost reduction opportunities, experience curves can be valuable tools for assessing future PFF production cost development in Sweden. A methodological issue that needs to be further explored is how learning took place between Sweden and other countries, especially with Finland, and how the development of technology and PFF production in these countries should be combined with the Swedish experiences. This would allow the utilization of the experience curve concept to estimate cost developments also in other countries with a large potential to supply PFF, but with less developed PFF supply systems.     

Attitudes towards on-land and offshore wind power development in Denmark; choice of development strategy

Wind power generation is expected to increase significantly in the near future. Owing to the increasingly limited possibilities for using on-land turbines, offshore wind generation is a potential alternative. However, wind turbines located offshore are still associated with visual disamenities potentially making offshore location a less attractive alternative to on-land wind power generation. The present paper analyses attitudes towards both on-land and offshore wind power development using a probit model. It also discusses the elicited determinants of attitude in relation to developing wind power on-land or offshore. Compared to other papers on attitude, the paper is unique in the sense that the Danish population has considerable experience with the different impacts associated with wind turbines compared to most of the other countries investing in wind power generation. This is particularly evident with regards to offshore development. The paper establishes that whilst offshore wind farms are preferred to on-land development, the results also imply that on-land development is still a feasible alternative. In that relation, differences in wind power generation costs and the substitution of smaller on-land turbines with fewer but larger turbines might make on-land development even more attractive. On a more detailed level, younger respondents are more positive towards wind power than older respondents. Interestingly, respondents living close to either on-land or offshore wind turbines did not display a more negative attitude towards wind power generation when compared to respondents who were not living close to wind turbines.     

Modeling noise and lease soft costs improves wind farm design and cost-of-energy predictions

The Department of Energy uses the metric Cost-of-Energy to assess the financial viability of wind farms. Non-hardware costs, termed soft costs, make up approximately 21% of total cost for a land-based farm, yet are only represented with general assumptions in models of Cost-of-Energy. This work replaces these assumptions with a probabilistic model of the costs of land lease and noise disturbance compensation, which is incorporated into a wind-farm-layout-optimization-under-uncertainty model. These realistic representations are applied to an Iowa land area with real land boundaries and house locations to accentuate the challenges of accommodating landowners. The paper also investigates and removes a common but unnecessary term that overestimates cost-savings from installing multiple turbines. These three contributions combine to produce COE estimates in-line with industry data, replacing “soft” assumptions with specific parameters, identify noise and risk concerns prohibitive to the development of profitable wind farm. The model predicts COEs remarkably close to real-world costs. Wind energy policy-makers can use this model to promote new areas of soft-cost-focused research.     

Evaluation of small wind turbines in distributed arrangement as sustainable wind energy option for Barbados

The island of Barbados is 99% dependent on fossil fuel imports to satisfy its energy needs, which is unsustainable. This study proposes a 10 MW distributed wind energy scheme using micro wind turbines (WT) of horizontal (HAWT) and vertical axis (VAWT) configurations. These units are rated less than 500 W, and the scheme is hereafter referred to as mWT10. mWT10 is compared to the proposed 10 MW medium WT farm by the Barbados Light & Power Company (BL&P). The economic bottom line is the levelized cost of electricity (LCOE). The results highlight the BL&P proposal as the best economic option at BDS$0.19 per kWh, while that of both mWT10 configurations exceeds the conventional cost of BDS$0.25 by two to nine times. This is attributed to significantly higher relative installation and operational costs. However, the financial gap between mWT10 LCOE and the retail price of electricity is much smaller due to a large fuel surcharge passed on to each customer. Annual additional benefits of using wind energy include: greenhouse gas emissions savings of 6–23 kt of carbon dioxide; and anavoided fuel costs of BDS$1.5–5.3 million.

The distributed mWT10 using HAWTs competes directly with the BL&P farm, however, it provides these benefits without the visual or ecological impacts of the larger machines. Conversely, VAWTs have features that favour a visually discrete and widely repeatable scheme but suffer relatively high costs. Therefore, this study illustrates the great potential of small wind turbines to be competitive with conventional wind farms, thus challenging the small wind industry to meet its potential by producing reliable and robust machines at lower cost.     

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.     

Site‐specific Design Optimization of Wind Turbines

This article reports results from a European project, where site characteristics were incorporated into the design process of wind turbines, to enable site‐specific design. Two wind turbines of different concept were investigated at six different sites comprising normal flat terrain, offshore and complex terrain wind farms. Design tools based on numerical optimization and aeroelastic calculations were combined with a cost model to allow optimization for minimum cost of energy. Different scenarios were optimized ranging from modifications of selected individual components to the complete design of a new wind turbine. Both annual energy yield and design‐determining loads depended on site characteristics, and this represented a potential for site‐specific design. The maximum variation in annual energy yield was 37% and the maximum variation in blade root fatigue loads was 62%. Optimized site‐specific designs showed reductions in cost of energy by up to 15% achieved from an increase in annual energy yield and a reduction in manufacturing costs. The greatest benefits were found at sites with low mean wind speed and low turbulence. Site‐specific design was not able to offset the intrinsic economic advantage of high‐wind‐speed sites. It was not possible to design a single wind turbine for all wind climates investigated, since the differences in the design loads were too large. Multiple‐site wind turbines should be designed for generic wind conditions, which cover wind parameters encountered at flat terrain sites with a high mean wind speed. Site‐specific wind turbines should be designed for low‐mean‐wind‐speed sites and complex terrain. Copyright © 2002 John Wiley & Sons, Ltd.     

Wind farm—A power source in future power systems

The paper describes modern wind power systems, introduces the issues of large penetration of wind power into power systems, and discusses the possible methods of making wind turbines/farms act as a power source, like conventional power plants in power systems. Firstly, the paper describes modern wind turbines and wind farms, and then introduces the wind power development and wind farms. An optimization platform for designing electrical systems of offshore wind farms is briefed. The major issues related to the grid connection requirements and the operation of wind turbines/farms in power systems are illustrated.     

Maximizing the returns of LIDAR systems in wind farms for yaw error correction applications

Wind energy is an important source of renewable energy with significant untapped potential around the world. However, the cost of wind energy production is high, and efforts to lower the cost of energy generation will help enable more widespread use of wind energy. Yaw error reduces the efficiency of turbines as well as lowers the reliability of key components in turbines. Light detection and ranging (LIDAR) devices can correct the yaw error; however, they are expensive, and there is a trade‐off between their costs and benefits. In this study, a stochastic discrete‐event simulation was developed that models the operation of a wind farm. We maximize the net present value (NPV) changes associated with using LIDAR devices in a wind farm and determine the optimum number of LIDAR devices and their associated turbine stay time as a function of number of turbines in the wind farm for specific turbine sizes. The outcome of this work will help wind farm owners and operators make informed decisions about purchasing LIDAR devices for their wind farms.     

Dynamic models of wind farms with fixed speed wind turbines

The increasing wind power penetration on power systems requires the development of adequate wind farms models for representing the dynamic behaviour of wind farms on power systems. The behaviour of a wind farm can be represented by a detailed model including the modelling of all wind turbines and the wind farm electrical network. But this detailed model presents a high order model if a wind farm with high number of wind turbines is modelled and therefore the simulation time is long. The development of equivalent wind farm models enables the model order and the computation time to be reduced when the impact of wind farms on power systems is studied. In this paper, equivalent models of wind farms with fixed speed wind turbines are proposed by aggregating wind turbines into an equivalent wind turbine that operates on an equivalent wind farm electrical network. Two equivalent wind turbines have been developed: one for aggregated wind turbines with similar winds, and another for aggregated wind turbines under any incoming wind, even with different incoming winds.The proposed equivalent models provide high accuracy for representing the dynamic response of wind farm on power system simulations with an important reduction of model order and simulation time compare to that of the complete wind farm modelled by the detailed model.     

Innovation and the price of wind energy in the US

In the last ten years, the wind energy industry has experienced many innovations resulting in wider deployment of wind energy, larger wind energy projects, larger wind turbines, and greater capacity factors. Using regression analysis, this paper examines the effects of technological improvements and other factors on the price of wind energy charged under long-term contracts in the United States. For wind energy projects completed during the period 1999–2006, higher capacity factors and larger wind farms contributed to reductions in wind energy contract prices paid by regulated investor owned utilities in 2007. However, this effect was offset by rising construction costs. Turbine size (in MW) shows no clear relationship to contract prices, possibly because there may be opposing factors tending to decrease costs as turbine size increases and tending to increase costs as turbine size increases. Wind energy is generally a low-cost resource that is competitive with natural gas-fired power generation.     

Adding wind power to a wind-rich grid: Evaluating secondary suitability metrics

As the quantity of renewable electricity generation from wind farms increases in a region, the costs associated with integrating it into the broader electricity system also grow. This is primarily due to the need for dispatchable generators that vary power output to compensate for wind farm power variations. Such “balancing services” are an economic cost to the system that is typically not passed on to wind farms. We propose including the use of technical merits other than capacity factor and cost of energy for evaluating new wind farm sites and present a new graphical geospatial method, with the intention of identifying sites that minimize the need for additional electricity balancing service and transmission congestion. Specifically, locations with low correlation to existing wind farms, locations with high correlation to load, locations with high characteristic power time-shift from existing wind farms, and locations that relieve or do not negatively impact electricity transmission congestion are identified. A geospatial Venn diagram-based method of visualization is presented. These methods will equip regional planners with new tools to encourage wind farm development in areas that benefit the electricity grid beyond the lowest bid price.     

Optimization of cable layout designs for large offshore wind farms

Installation of a wind farm exposes several problems such as site selection, placement of wind turbines in the site, and designing of cable infrastructure within the farm. The latter problem, called cable layout design, is the determination of cable connections among turbines and one or more transmitters such that energies generated by turbines will be sent through the cable routes, and eventually gathered at the transmitter(s). This problem is especially important for offshore wind farms where the featured and expensive cables are used. The main objective of the present study is to address the cable layout design problem of offshore wind farms to reduce cable costs in the design using optimization-based approaches. The problem, firstly, is modelled as a mixed integer linear program (MIP) under a set of real-life constraints such as different cable and transmitter types and non-crossing connections between the turbines. Then, a novel mathematical model, which is a modification of the MIP model by imposing several heuristic rules, is proposed to solve the layout problem of large offshore wind farms. Experiments on a set of small- and moderate-sized test instances reveal that the heuristic model, MIP_H, reduces the computer time nearly 55% compared to that of MIP model while the average cable costs generated by the models are close to each other. MIP_H, besides its efficiency, provides more cost-effective layouts compared to MIP model for large-sized real-life examples. Additionally, a comparative study on MIP_H and existing methods in the literature shows that MIP_H is able to solve all instances of the real-life examples providing less cable costs in average.     

Modelling the effects of environmental conditions on wind turbine failures

Operation and maintenance is one of the main cost drivers of modern wind farms and has become an emerging field of research over the past years. Understanding the failure behaviour of wind turbines (WTs) can significantly enhance operation and maintenance processes and is essential for developing reliability and strategic maintenance models. Previous research has shown that especially the environmental conditions, to which the turbines are exposed to, affect their reliability drastically. This paper compares several advanced modelling techniques and proposes a novel approach to model WT system and component failures based on the site‐specific weather conditions. Furthermore, to avoid common problems in failure modelling, procedures for variable selection and complexity reduction are discussed and incorporated. This is applied to a big failure database comprised of 11 wind farms and 383 turbines. The results show that the model performs very well in several situations such as modelling general WT failures as well as failures of specific components. The latter is exemplified using gearbox failures.     

Optimal turbine spacing in fully developed wind farm boundary layers

As wind farms become larger, the asymptotic limit of the ‘fully developed’, or ‘infinite’, wind farm has been receiving an increased interest. This limit is relevant for wind farms on flat terrain whose length exceeds the height of the atmospheric boundary layer by over an order of magnitude. Recent computational studies based on large eddy simulation have identified various mean velocity equilibrium layers and have led to parameterizations of the effective roughness height that allow the prediction of the wind velocity at hub height as a function of parameters such as wind turbine spacing and loading factors. In the current paper, we employ this as a tool in making predictions of optimal wind turbine spacing as a function of these parameters, as well as in terms of the ratio of turbine costs to land surface costs. For realistic cost ratios, we find that the optimal average turbine spacing may be considerably higher than that conventionally used in current wind farm implementations. Copyright © 2011 John Wiley & Sons, Ltd.