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The Government's aim to curb CO₂ emissions from energy production has resulted in the growth of a new environmental feature; the wind turbine. Whilst this may help tackle climate change, there is concern that the visual and aural presence of these turbines could have a negative impact on house prices. Opinion studies undertaken within the UK appear to show significant variations in attitudes towards wind farms in different locations (in particular between Scotland and southern England) and at different stages during the development process. However, to date, no research has established the actual impact on proximate house values. Therefore, the purpose of this study, sponsored by the RICS, is to develop a methodology to measure the likely impact of onshore wind farms on house prices in the UK.

This study focused on residential property surrounding two wind farms in Cornwall. Transaction data for 1,052 house sales completed between 2000 and 2004 were obtained and analysed using regression modelling and comparative sales analysis. A second study undertook an analysis of the planning objections to wind farms in this location.

The analysis of transaction data found some correlation between distance from a wind farm, and value. However, the data were insufficiently detailed to draw any sound conclusions. The analysis of planning objections revealed that 95 percent of objections came from people living outside Cornwall.

Whilst the methodology is sound, the available data were limited to house type and selling price, and therefore not sufficiently detailed to highlight any small changes in value.

The paper establishes general criteria which could be used to evaluate the potential impact of onshore wind farms on property values.

This chapter examines why U.S. offshore wind farms do not exist and identifies sites most suitable for development based on European offshore wind farms. A survey of current literature indicates that U.S. development is stalled due to a lack of government and financial support. The literature identifies common attributes associated with the successful deployment of European offshore farms and provides a basis for a multi-criteria decision analysis of potential U.S offshore wind farm sites. A review of European wind farms indicates that a small, 10–50 MW farm located in shallow waters of less than 20 m might be more successful than previous U.S. development efforts. The review also identifies common European attributes deemed critical for success. These attributes are modified, taking into account unique U.S. factors, and a set of nine critical attributes are derived for use in a multi-criteria decision analysis model of suitable U.S. locations. The nine critical attributes (wind quality, water depth, shore distance, state support, public support, industrial support, population density, weather, and energy costs), along with associated utility function values, are applied to 23 past and current proposed U.S. sites. The model identified three sites, in Galveston Island, TX, Port Isabel, TX, and Block Island, RI, as being most favorable for a small wind farm.

The rapid rising of renewable energy sources particularly wind energy cannot be ignored. The numerical increase in wind energy farms throughout the world is the best example. The purpose of this paper is to assess the basic question of whether wind characteristics affect the performance and cost of energy. The importance of this question cannot be ruled out while comparing renewable energy to a conventional form of energy more specifically especially for the developing country where the cost of energy is very high.

The research design of this paper is consists of an assessment of local wind characteristics of the wind farm site using Weibull k and c parameters. The performance model is used to assess the performance of the wind turbine (WT) corresponding to local wind characteristics. The wind correlation with WT in terms of changing wind speed has been assessed to quantify the effects of wind speed on the WT behavior and failure of WT components. Similarly, the power curve of WT is assessed and compared with the International Electrotechnical Commission standards 61400-12-2. The WT power coefficient and tip speed ratio corresponding to wind speed is also investigated. The energy volume and cost of energy lost model is used to determine the cost and volume loss of energy/kWh of the wind farm.

The findings of practical wind farms showed that the wind conditions of the site are showing a strong tendency that can be determined from the results of Weibull k and c parameters. The k and c parameters are observed to be 3.44 and 9.16 m/s, respectively, for a period of a year. The standard deviation is observed to be 2.56 for a period of a year. WT shows the efficient behavior can be obtained from the power coefficient and tip speed of WT at different wind speeds. Also, wind farm observation showed that to be some increasing wind speed cause of based WT component failures. The results of energy volume and cost/kWh assessment showed that the major portion of energy volume and cost of energy is lost owing to network, voltage dip and frequency surge, electrical and mechanical components failures.

Generally, it can be concluded that the WTs are now able to cope with variable wind speeds. However, the results of this paper are showing that WT performance and availability decreased due to increased wind speeds. It can also be a reason to decreased volume and increase the cost of energy/kWh.

The purpose of this paper is to discuss how wind farms attract wind turbine manufacturers to get involved in wind turbines’ maintenance service with revenue sharing contract of bundled service under which the background of operation and maintenance (O&M) aftermarket of wind turbine exists. The authors also try to extend the results to the application of product plus service business mode on large-scale equipment O&M service. At present, Chinese wind power industry is suffering from production capacity redundancy. The profit levels for both wind farm and wind turbine manufacturers are relatively low. It is significant for Chinese wind power industry development to coordinate the supply chain of wind power in order to reduce O&M costs and increase revenues.

The present paper discusses product plus aftermarket service contract design on the background of closed-loop product service chain and uncertain equipment demand using revenue sharing contract model.

If centralized decision making is assumed, the authors find that the wind turbine order increases as the aftermarket service effort level and aftermarket service profit increase; aftermarket service effort level is positively correlative to the service efficiency. On the other hand, if decentralized decision making is assumed, the wind turbine order increases as share of the aftermarket service chain by manufacturer to wind farm increases and share of product supply chain by wind farm to manufacturer decreases. The optimal effort level of wind farm increases as the share of aftermarket service chain increases while the optimal effort level of the manufacturer is a concave function of share of aftermarket service chain if service quality linear correlates with effort level. Meanwhile, the authors find that the revenues of the product supply chain and aftermarket service chain have a concave relationship. This relationship is not affected by the format of relationship between service quality and effort level (linear or exponential).

The results could potentially be used to provide the wind turbine manufacturer with a greater profit space and satisfy wind farm’s equipment maintenance demand at the same time. It can also guide the practice of revenue sharing in the aftermarket service and manufacturing servitization.

In this model, the authors assumed that both the forward revenue sharing of power generation by wind farm to manufacturer and the backward revenue sharing of maintenance service by the manufacturer to wind farm exist in closed-loop product service chain. Then the authors discussed channel coordination of such cross-revenue sharing contract.

Although the wind power industry has been booming in China during the last decade, the development of wind turbine aftermarket service is still lagging behind, which seriously affects the operational efficiency of wind farms. If wind turbine manufacturers get involved in the aftermarket, the service pricing policy will impact the profits of both the manufacturer and the wind farm. Therefore, it is necessary to discuss an optimal service pricing strategy in the wind turbine aftermarket and design a method to improve electricity generation efficiency through service contract design. The paper aims to discuss these issues.

In order to decide the maintenance quantity and channel effort level, the authors design a normal Stackelberg game and an efficiency value-added revenue-sharing contract and discuss two kinds of revenue increment sharing models under situations, in which the supply chain’s leaders are the wind farm and the wind turbine manufacturer, respectively.

The results show that in either case, there exist optimal power generation revenue-sharing ratios that can maximize profit. At the same time, the authors outline an optimal service pricing policy, maintenance demand policy and channel service effort-level policy. The results summarize the influences of wind aftermarket services on wind farms’ and wind turbine manufacturers’ profit, which provides managerial insights into the process of manufacturing servitization.

The manufacturer’s channel effort level will influence the power generation increments very much, so the authors have developed a mechanism to stimulate the manufacturer improving the efficiency of aftermarket services.

Taking the power generation increment revenue as the profit increment function, the authors discuss the influence of service price on the profit increment of the wind farm and the wind turbine manufacturer and also consider the influence of service price on the wind farms maintenance quantity and wind turbine manufacturers channel effort level.

Maintenance planning is a complicated decision-making process that involves the major stakeholders and the main life-cycle phases of an engineering system. The purpose of this paper is to propose an availability-centred maintenance planning approach for offshore wind farms, with special focus on the early system design phase.

The proposed approach is based on a stepwise procedure that integrates logistics consideration into reliability-centred maintenance. For each step, the essential methods for systematic analysis and documentation are introduced.

Practical information from current offshore wind farms and lessons learned from relevant industries are included to exemplify and justify the implementation of the proposed approach. In a general way, the approach shows that valuable input can be provided to decision making about maintainability and maintenance planning. Furthermore, the approach facilitates the initial maintenance plan to be adjusted and improved upon as additional operating experience becomes available.

Offshore wind energy is still an industry in its infancy with an attendant high degree of confidentiality. There is scarcely any detailed practical information available for the production of a case study on this topic. However, the current paper’s theoretical basis may be applied to identify current and future knowledge gaps, for the development of more detailed guidelines as established in the further research.

Maintenance planning of offshore wind farms is an area of current interest, although often the focus is on achieving cost reductions and not on the formal development of such a systematic approach as conceived in this paper.

The purpose of this paper is to analyze wind climate parameters and performance functions, on the basis of two years of data, and reliability of Pakistan’s first wind farm located at Jhimpir, Sindh.

The methodology covers assessment of wind climate parameters including wind variation at different hub heights, wind shear and diurnal wind shear. In addition, a performance assessment of a wind farm on the basis of technical and real availability, capacity factor and failure rate of mechanical and electrical components has been conducted. The Weibull method has been used for reliability analysis. The maintenance model is proposed for improving the performance. Last is about annual energy volume lost and of financial constraints’ assessment.

The monthly mean wind variation at heights of 80, 60 and 30 m was found to be 8, 6.9 and 5.9 m/s, respectively. The monthly mean wind shear coefficient was found to be 0.2419. The performance assessment of the wind farm includes technical and real availability, and the capacity factor was found to be 97, 90 and 35.5 per cent, respectively. The failure rate found in the first and second year was 8 and 14 per cent, respectively. Reliability decreased from the first year to the second year, i.e. 0.89 to 0.71 per cent. The components’ failure frequency rose to 57.2 per cent in the second year. The lost energy production due to electrical and mechanical failures was 27.241 GWh in two years that cost Pakistani Rs. 329.8m.

The results of the assessment show that a wind farm needs drastic maintenance strategies to maximize the its performance.

Conditions monitoring system (CMS) is a tool for describing the present condition of the components of a system. To achieve this objective, there is a need to develop an efficient fault prediction algorithm. This paper seeks to address this issue.

The paper analyses four real wind farms with control charts of indices derived from UNE EN15341:2008 standard indicators, as the main CMS algorithm to define which index must be considered for improving wind farm maintenance and related costs.

The findings show that climatic conditions are related to maintenance cost indices. Employing the statistical control process of various wind energy converter (WEC) indices proposed by wind farm operators is an adequate procedure to monitor and control wind farm performance. In particular, only the maintenance cost index and the hourly maintenance cost index presented a clear relationship with respect to weather conditions.

Climatic conditions must form the basis for organising maintenance activities. Despite this, future maintenance models must be centred on indices obtained from experience, like the maintenance cost index and hourly maintenance cost index, and not solely in general indicators defined by standards.

A practical case study of wind farm maintenance based in the new UNE EN15341:2008 standard and wind farm operators experience is shown, defining real indices to be employed in future maintenance procedures.

As the interest in renewable energy increases and the number of federal and state incentives to support renewable energy has also grown in recent years, it seems worthwhile to explore the economics of using small wind energy systems to offset electricity costs on farms. The purpose of this paper is to explore the economics of small wind turbine installations on a dairy in Michigan through case study analysis.

An Excel‐based capital budgeting model is developed that contains two sub‐modules: one that estimates the value of the wind energy based on the measured wind resource, and an investment module that includes factors such as investment cost, financing parameters, sales of electricity; grants and tax credits and tax information. Cases using 20 and 50 kW turbine systems are analyzed.

The results of the case studies show that in a favorable wind resource, the federal tax and United States Department of Agriculture incentives as well as state policies such as net metering can make wind turbines a good investment with an internal rate of return of 12.5 percent in this example. However, if the wind resource is not sufficient, even favorable renewable energy policies will not offset the lost value of the power generation, and thus a wind turbine will be a poor investment decision. Farm businesses should carefully consider all factors before investing in a wind turbine.

This paper is the first in recent years to combine capital budgeting analysis, wind resource data and the implications of federal and state policies to determine if small wind turbines are a sound investment decision for farm businesses.

The purpose of this paper is to assess model risk with regard to wind energy output in monthly cash flow models for the purpose of valuation and risk assessment of wind farm investments, where only a few approaches exist in the literature.

This paper focuses on the risk-return characteristics of this investment from the perspective of private and institutional investors and takes into account several risks, in particular the resource risk related to the uncertainty of the monthly wind energy produced. To this end, this paper presents different approaches for modeling monthly wind power output and assesses the impact of three selected models with different properties on the investment’s risk-return characteristics by means of a stochastic discounted cash flow model. In addition, the model considers the possibility of a joint operation of the wind farm with a pumped hydro storage system to reduce risk and improve profits.

The results show that the (non-)consideration of seasonality of the monthly wind energy produced considerably influences the risk-return characteristics, but that principal developments dependent on input parameters and model variables remain similar.

This paper contributes to the literature by presenting different approaches for modeling the monthly wind energy produced based on direct models of the wind energy output, which are rare in the existing literature. Further, their impact on risk-return characteristics of a wind farm investment is analyzed, and thus, related model risk is assessed.