OVERVIEW
For the past decades, ground-based conventional wind turbine systems have been in use in wind power generation. However, they face several limitations, e.g. visual and noise impacts, space requirement, intermittency, location restrictions linked to environmental and permit issues, and lastly shadows. With improved technology and increased funding, research into wind harnessing is now being directed into high altitude winds to minimise the limitations.
GIS (Geoinformation Systems) enables the advanced processing, analysis and mapping of potential areas to deploy Airborne wind energy systems (infrastructure)- AWESs. The study is performed with datasets extracted from 10 years (2007–2016) with a 6-hour spatial interval and altitudes between 200m-1000m with 100m interval.
OBJECTIVE
The main objectives of this project were to identify desirable areas for the deployment of Airborne wind energy systems and to examine the optimal altitude range for the implementation of AWESs.
METHODS AND RESULTS
The data obtained was of GRID format, which is converted into NPZ format for easy usage. For vertical dimensions, the already reanalysed dataset was in atmospheric pressure, which by using the hydrostatic and gas law equations is converted to meters.
The variables in the extracted gridded wind data include atmospheric pressure, time, geopotential, temperature, wind speed and direction. With the use of wind speed, mass, area and volume, wind power density is computed. Time series analysis is performed to extract the trend, seasonality and irregularity. Statistical analysis is done to determine
a). The regression and correlations between wind speed and wind power, and height and with power,
b). The Weibull probability function is done to ascertain the best approximate for the distribution of wind speeds over time
c). Other statistical quantities include mean and standard deviation.
With constraints imposed by the government, e.g. distance from transport infrastructure, electricity grid, settlement and urban area, and airports, military training areas and controlled airspace etc. Buffering is done to these areas and locations that are constraints.
The power output highly depends on the strength of wind speed, with the decrease in wind speed (Southern Germany), so the decline of wind power output. The wind speed increases from the south, and so is the expected wind power at this level, its both economic and viable to choose Northern Germany as the best position to implement AWESs.
Results
Wind power generated from 600m to 1000m agl (above ground level) shows a relatively constant and high AWE Production.
Ps/ This was my Masters Thesis at Tu Berlin
