Wind energy enables electric generation without adding additional pollution to the environment but entails substantial initial turbine, setup, and land investment. Most turbine setups cannot generate electricity to their full capacity due to poor installation planning, but a proper installation plan can generate about 1 million GW of wind energy from existing land coverage and provide an optimal investment return. This paper studies existing turbine setups using a dataset from the U.S. Wind Turbine Association. This dataset contains data from 58,449 turbines. We conduct three sets of experiments using data mining techniques, the various factors affecting turbines, and Tableau. The performance of existing turbines is analyzed for metrics including their rotor sweep area, location, manufacturer, year of manufacture, and count. The study also employs various classification algorithms based on data mining to analyze turbine performance based on the dataset. The study recommends the best algorithms for the considered metrics and provides suggestions for future research.
Volume 11 | 06-Special Issue
Pages: 399-413