Variation in energy intake and basal metabolic rate of a bird migrating in a wind tunnel

1. We studied the changes in body mass, metabolizable energy intake rate (ME) and basal metabolic rate (BMR) of a Thrush Nightingale, Luscinia luscinia, following repeated 12-h migratory flights in a wind tunnel. In total the bird flew for 176 h corresponding to 6300 km. This is the first study where the fuelling phase has been investigated in a bird migrating in captivity.

2. ME was very high, supporting earlier findings that migrating birds have among the highest intake rates known among homeotherms. ME was significantly higher the second day of fuelling, indicating a build-up of the capacity of the digestive tract during the first day of fuelling.

3. Further indications of an increase in size or activity level of metabolically active structures during fuelling come from the short-term variation in BMR, which increased over the 2-day fuelling period with more than 20%, and in almost direct proportion to body mass. However, mass-specific BMR decreased over the season.

4. The patterns of mass change, ME and BMR of our focal bird following two occasions of 12-h fasts were the same as after flights, indicating that fast and flight may involve similar physiological processes.

5. The relatively low ME the first day following a flight may be a contributing factor to the well-known pattern that migrating birds during stopover normally lose mass the first day of fuelling.

Wingbeat frequency and the body drag anomaly: wind-tunnel observations on a thrush nightingale (Luscinia Luscinia) and a teal (Anas crecca)

A teal (Anas crecca) and a thrush nightingale (Luscinia luscinia) were trained to fly in the Lund wind tunnel for periods of up to 3 and 16 h respectively. Both birds flew in steady flapping flight, with such regularity that their wingbeat frequencies could be determined by viewing them through a shutter stroboscope. When flying at a constant air speed, the teal's wingbeat frequency varied with the 0.364 power of the body mass and the thrush nightingale's varied with the 0.430 power. Both exponents differed from zero, but neither differed from the predicted value (0.5) at the 1 % level of significance. The teal continued to flap steadily as the tunnel tilt angle was varied from -1° (climb) to +6° (descent), while the wingbeat frequency declined progressively by about 11%. In both birds, the plot of wingbeat frequency against air speed in level flight was U-shaped, with small but statistically significant curvature. We identified the minima of these curves with the minimum power speed (Vmp) and found that the values predicted for Vmp, using previously published default values for the required variables, were only about two-thirds of the observed minimum-frequency speeds. The discrepancy could be resolved if the body drag coefficients (CDb) of both birds were near 0.08, rather than near 0.40 as previously assumed. The previously published high values for body drag coefficients were derived from wind-tunnel measurements on frozen bird bodies, from which the wings had been removed, and had long been regarded as anomalous, as values below 0.01 are given in the engineering literature for streamlined bodies. We suggest that birds of any size that have well-streamlined bodies can achieve minimum body drag coefficients of around 0.05 if the feet can be fully retracted under the flank feathers. In such birds, field observations of flight speeds may need to be reinterpreted in the light of higher estimates of Vmp. Estimates of the effective lift:drag ratio and range can also be revised upwards. Birds that have large feet or trailing legs may have higher body drag coefficients. The original estimates of around CDb=0.4 could be correct for species, such as pelicans and large herons, that also have prominent heads. We see no evidence for any progressive reduction of body drag coefficient in the Reynolds number range covered by our experiments, that is 21600-215 000 on the basis of body cross-sectional diameter.

Hybrid technique of ant colony and particle swarm optimization for short term wind energy forecasting

Wind farms are producing a considerable portion of the world renewable energy. Since the output power of any wind farm is highly dependent on the wind speed, the power extracted from a wind park is not always a constant value. In order to have a non-disruptive supply of electricity, it is important to have a good scheduling and forecasting system for the energy output of any wind park. In this paper, a new hybrid swarm technique (HAP) is used to forecast the energy output of a real wind farm located in Binaloud, Iran. The technique consists of the hybridization of the ant colony optimization (ACO) and particle swarm optimization (PSO) which are two meta-heuristic techniques under the category of swarm intelligence. The hybridization of the two algorithms to optimize the forecasting model leads to a higher quality result with a faster convergence profile. The empirical hourly wind power output of Binaloud Wind Farm for 364 days is collected and used to train and test the prepared model. The meteorological data consisting of wind speed and ambient temperature is used as the inputs to the mathematical model. The results indicate that the proposed technique can estimate the output wind power based on the wind speed and the ambient temperature with an MAPE of 3.513%.

A new fuzzy-based combined prediction interval for wind power forecasting

This paper makes use of the idea of prediction intervals (PIs) to capture the uncertainty associated with wind power generation in power systems. Since the forecasting errors cannot be appropriately modeled using distribution probability functions, here we employ a powerful nonparametric approach called lower upper bound estimation (LUBE) method to construct the PIs. The proposed LUBE method uses a new framework based on a combination of PIs to overcome the performance instability of neural networks (NNs) used in the LUBE method. Also, a new fuzzy-based cost function is proposed with the purpose of having more freedom and flexibility in adjusting NN parameters used for construction of PIs. In comparison with the other cost functions in the literature, this new formulation allows the decision-makers to apply their preferences for satisfying the PI coverage probability and PI normalized average width individually. As the optimization tool, bat algorithm with a new modification is introduced to solve the problem. The feasibility and satisfying performance of the proposed method are examined using datasets taken from different wind farms in Australia.

Wind Power in Maine: Balancing Conservation and Energy Production

An expedited permitting area has been created to facilitate the development of wind power projects in Maine. The purpose of this project was to investigate the impact of removing areas of conservation interest from the expedited permitting area. We found that the removal of these areas impacts the total wind potential of the state, in an amount proportional to the size of the area removed. The impact on the total wind potential ranged from 0.46-29.0% decrease, depending on the calculation scenario used. These findings may have implications for future policy decisions concerning wind power development.

Wind Turbine Visibility on the Colby Campus

This project was designed to demonstrate the visibility of potential future wind turbines built on the Colby campus. We conducted viewshed analyses in ArcGIS on three different potential turbine sites to determine the visibility of the turbines within a 10km radius. We found that the Runnals hill turbine would be visible to the largest area and the largest number of residents.

A Visibility Analysis of the Cape Wind Project

Cape Wind has proposed a wind farm of 130 turbines on Horseshoe Shoal in the center of Nantucket Sound. A prominent concern about the project is the impact the visibility of the turbines will have on the region's tourism industry and property values. It is feared that their presence will diminish the value of the pristine coastline that has attracted vacationers to Cape Cod for generations. In this project, we assess the extent to which Cape Cod, Martha's Vineyard, and Nantucket will be visually affected by the wind farm. It was completed using a Viewshed Analysis in the GIS program, ArcMap, from the surface, mean, and maximum height of the towers. These Viewsheds were combined to give a comprehensive perspective of which areas are able to see the highest percent of the wind farm. Finally, a weighted land use value was applied to the Viewshed to account for the impact of land use on the ability to see the project. The objective of this analysis is to provide a visual representation of how great an influence the wind farm will in fact have on Cape Cod.

Gulf of Mexico's Offshore Oil Platform Wind Potential

There are over 6000 natural resource drilling platforms in the Gulf of Mexico, all of which will become obsolete once their deposits are extracted. This study examined one of the possible alternate uses for these platforms, wind power potential. Using ArcGIS the number of platforms was reduced by weighting their distance from National Data Buoy Center wind speed collection points and water depth. Calculations were done to assess the optimal sites remaining, as well as provide an estimate of the energy potential for each site. Data for this project was obtained from the Minerals Management Service (MMS), United States Geological Service (USGS), and National Data Buoy Center (NDBC). A major limitation of this project was a lack of NDBC wind speed buoys, creating large data gaps and excluding many oil rigs that have otherwise high energy potential.

Wind Power Suitability Analysis for the Gulf of Maine

This map shows one option for a viable energy source that is clean, free and endless: wind power. This map shows that the coast of Maine has the potential space and wind speed to be a location for wind farms. Four NOAA buoys placed in different locations along the Maine coast are the source of the wind speed data for this project. The average wind speed of every ten minutes of every day for the year 2004 were averaged so that each buoy was represented by one number of wind speed measured in meters/ second. The values in between these four buoys were estimated, or interpolated, using ArcGIS. Other factors that I took into consideration during this lab were distance from airports (no wind farm can be with in a three mile radius of an airport ) and distance from counties (no one wants an offshore wind farm that obstructs their view). I calculated the most appropriate locations for a wind farm in ArcGIS, by adding these three layers. The final output shows an area along Mt. Desert to be the most appropriate for development.

Type 13 Design A Starboard Side; SS Northern Wind

Stamp of "163"; Discontinued stamp JUL 29 1918

Type 13 Design A Port Side; SS Northern Wind

Stamp of "166"; Discontinued stamp JUL 29 1918