Wind Turbines and Coastal Recreation Demand

We examine the impact of coastal wind turbines on coastal tourism and recreation for residents of the northern CAMA counties in North Carolina. A combination of telephone and web survey data are used to assess the impact of coastal wind farms on trip behavior and site choice. Most of the respondents to our telephone survey claim to support offshore wind energy development, and independent survey data suggest that the observed levels of support may be indicative of the broader population in this region. Overall, we find very little impact of coastal wind turbines on aggregate recreational visitation; loss in consumer surplus associated with wide spread wind development in the coastal zone is insignificant at $17 (or about 1.5$55 per household. On average, we find no evidence of aversion to wind farms 4 miles out in the ocean, or for wind farms located in coastal estuaries. For all wind farm scenarios, we find evidence of preference heterogeneity– some respondents find this appealing while others find it aversive. Key Words: Recreation demand, tourism, renewable energy

Remote data acquisition for condition monitoring of wind turbines

While the number of offshore wind turbines is growing and turbines getting bigger and more expensive, the need for good condition monitoring systems is rising. From the research it is clear that failures of the gearbox, and in particular the gearwheels and bearings of the gearbox, have been responsible for the most downtime of a wind turbine. Gearwheels and bearings are being simulated in a multi-sensor environment to observe the wear on the surface

Wind Energy and the Turbulent Nature of the Atmospheric Boundary Layer

Wind turbines operate in the atmospheric boundary layer, where they are exposed to the turbulent atmospheric flows. As the response time of wind turbine is typically in the range of seconds, they are affected by the small scale intermittent properties of the turbulent wind. Consequently, basic features which are known for small-scale homogeneous isotropic turbulence, and in particular the well-known intermittency problem, have an important impact on the wind energy conversion process. We report on basic research results concerning the small-scale intermittent properties of atmospheric flows and their impact on the wind energy conversion process. The analysis of wind data shows strongly intermittent statistics of wind fluctuations. To achieve numerical modeling a data-driven superposition model is proposed. For the experimental reproduction and adjustment of intermittent flows a so-called active grid setup is presented. Its ability is shown to generate reproducible properties of atmospheric flows on the smaller scales of the laboratory conditions of a wind tunnel. As an application example the response dynamics of different anemometer types are tested. To achieve a proper understanding of the impact of intermittent turbulent inflow properties on wind turbines we present methods of numerical and stochastic modeling, and compare the results to measurement data. As a summarizing result we find that atmospheric turbulence imposes its intermittent features on the complete wind energy conversion process. Intermittent turbulence features are not only present in atmospheric wind, but are also dominant in the loads on the turbine, i.e. rotor torque and thrust, and in the electrical power output signal. We conclude that profound knowledge of turbulent statistics and the application of suitable numerical as well as experimental methods are necessary to grasp these unique features (...)Comment: Accepted by the Journal of Turbulence on May 17, 201

Progress on the experimental set-up for the testing of a floating offshore wind turbine scaled model in a field site

This document describes design and realization of a small-scale field experiment on a 1:30 model of spar floating support structure for offshore wind turbines. The aim of the experiment is to investigate the dynamic behaviour of the floating wind turbine under extreme wave and parked rotor conditions. The experiment has been going on in the Natural Ocean Engineering Laboratory of Reggio Calabria (Italy). In this article, all the stages of the experimental activity are presented, and some results are shown in terms of motions and response amplitude operators. Finally, a comparison with corresponding results obtained using ANSYS AQWA software package is shown, and conclusions are drawn. The presented experimental set-up seems promising to test offshore floating structures for marine renewable energy at a relatively large scale in the Natural Ocean Engineering Laboratory field site

When a good is a bad (or a bad is a good) - analysis of data from an ambiguous nonmarket valuation setting

This paper analyses data from a contingent valuation experiment carried out in a context with large degree of preference heterogeneity and valuation ambiguity. Despite this challenge, by implementing estimation of an unrestricted valuation function on pooled data from two elicitation formats, utilizing all preference information available from the survey, we are able to estimate welfare measures with an acceptable degree of statistical confidence. It turns out that an offshore wind farm, a priori believed to constitute a bad that people would be willing to pay to avoid, instead was a good that people would be willing to forego under compensation. This was true on average but not for all study participants. Two key determinants of preferences were spatial proximity to the proposed wind farm and perceptions of the visual impacts of wind turbines. Individuals who would be near and thought wind turbines are “ugly” had a mean willingness to pay to avoid the wind farm of about $508 per household per year. In contrast, those who would be far away and perceived wind turbines to be “beautiful” had a negative mean willingness to pay to avoid the wind farm of about −$595 per household per year.publishedVersio

Failure mode identification and end of life scenarios of offshore wind turbines: a review

In 2007, the EU established challenging goals for all Member States with the aim of obtaining 20% of their energy consumption from renewables, and offshore wind is expected to be among the renewable energy sources contributing highly towards achieving this target. Currently wind turbines are designed for a 25-year service life with the possibility of operational extension. Extending their efficient operation and increasing the overall electricity production will significantly increase the return on investment (ROI) and decrease the levelized cost of electricity (LCOE), considering that Capital Expenditure (CAPEX) will be distributed over a larger production output. The aim of this paper is to perform a detailed failure mode identification throughout the service life of offshore wind turbines and review the three most relevant end of life (EOL) scenarios: life extension, repowering and decommissioning. Life extension is considered the most desirable EOL scenario due to its profitability. It is believed that combining good inspection, operations and maintenance (O&M) strategies with the most up to date structural health monitoring and condition monitoring systems for detecting previously identified failure modes, will make life extension feasible. Nevertheless, for the cases where it is not feasible, other options such as repowering or decommissioning must be explored

Methods to quantify avian airspace use in relation to wind energy development

It is likely that there will continue to be a substantial increase in the number of wind turbines as we aim to meet global energy demands through renewable sources. However, these structures can have adverse impacts on airborne wildlife, such as posing a potential collision risk with the turbine structure. A range of methods and technologies have been applied to the collection of bird flight parameters, such as height and speed, to improve the estimation of potential collision compared with traditional visual methods, but these are currently not applied in a consistent and systematic way. To this end, a systematic literature search was conducted to (1) examine the methods and technologies that can be used to provide bird flight data to assess the impact of wind energy developments and (2) provide an updated framework to guide how they might be most usefully applied within the impact assessment process. Four empirical measurement methods were found that improve the estimation of bird flight parameters: radar, telemetry, ornithodolite and LiDAR. These empirical sensor-based tools were typically more often applied in academic peer-reviewed papers than in report-based environmental statements. Where sensor-based tools have been used in the report-based literature, their inconsistent application has resulted in an uncertain regulatory environment for practitioners. Our framework directly incorporates sensor-based methods, together with their limitations and data requirements, from pre-deployment of infrastructure to post-consent monitoring of impacts. This revised approach will help improve the accuracy of estimation of bird flight parameters for ornithological assessment of wind energy. Sensor-based tools may not be the most cost-effective. However, a precedent has been set for wind energy development consent refusal based on ornithological impact assessment, and therefore the cost of collecting accurate and reliable flight data may be balanced favourably against the cost of development consent refusalacceptedVersio