An agglomerative hierarchical clustering tool for renewable energy sources

Abstract

The wind power based energy generation technologies are intensively studied in renewable energy generation issues since last century. The main demands directed to a renewable energy source are being reliable, sustainable and low-cost. Several studies are performed to increase the efficiency of an installed wind power plants. The preliminary analyses such as geographical structures, climate conditions, and land topography should be also considered during feasibility analyses of a wind plant. Although the obtained data could be processed by using numerical or various estimation methods, the data mining techniques provide more accurate results among others. In this study, the agglomerative hierarchical clustering tool is designed and is capable to process any data set supplied by expert to system. The case study is performed using monthly average wind speed data of Central Anatolia Region of Turkey in the paper. It is observed that the developed tool clusters the given sample data set in an efficient and successful way.