Using artificial neural networks to determine the location of wind farms. Miedzna district case study
Abstract The article concerns issues pertaining to of selecting suitable areas for wind farms. The basic assumption of the study was to take into account both criteria related to the profitability of this type of power plant, as well as public interest, which means the harmonious and not burdensome functioning of these installations for local communities. The problem of wind farm localization may be solved by the application of artificial neural networks (ANN) which are a computational intelligence element. In the conducted analysis, the possibility of wind farm localization was considered for the primary grid field with dimensions of 100 by 100 m. To prepare the training set, topographic vector data from the VMap L2 and SRTM (Shuttle Radar Topography Mission) digital terrain model were used. For each 100 meter x 100 meter grid, the input data was prepared, consisting of the factors which are important from the point of view of wind farm localization (forests, rivers, built up areas etc. Studies show that a properly trained neural network (using a representative number of samples and for the appropriate architecture) allows to process automation area classification in terms of placement on the wind turbines.