Dual-band Filtenna Array for WLAN Applications

This paper presents the design and results of a dual-band antenna array integrated with bandpass filters for WLAN applications. The array is fed with a single 50 Ω port and consists of two radiating elements; thereby having a 1x2 array structure. The two bands of the antenna array correspond to the two WLAN bands of 2.4 GHz and 5.8 GHz. A standalone array has first been designed. Other than the two fundamental resonant frequencies, the standalone array exhibits spurious harmonics at various other frequencies. For the suppression of these harmonics, the array has been integrated with two bandpass filters, centered at 2.4 GHz and 5.8 GHz. The resulting filtenna array was simulated, fabricated and measured. Obtained simulation and measurement results agree well with each other and have been presented to validate the accuracy of the proposed structure. Measured return loss of the structure shows dual-bands at 2.4 GHz and 5.8 GHz of more than 30 dB each and also a successful suppression of the spurious harmonics of the antenna array has been achieved. Radiation patterns have also been simulated and measured and both results shown. The gain and efficiency have also been presented; with the values being 6.7 dBi and 70% for the 2.4 GHz band and 7.4 dBi and 81% for the 5.8 GHz band respectively.

Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders (Belgium).