Data Analytics Information Support For Wind Energy Power Generation Business Management

Abstract

Wind Energy Power Generation Business basically involves converting the kinetic energy of the wind to electric energy using Wind Turbines Generator (WTG) and supplying the electric energy to the customer. The electric energy generated by these Wind turbines depends primarily on the speed of the wind. Since the wind speed varies from location to location and from season to season, the power generation of the wind turbine also varies accordingly. In order to give a realistic commitment to customer regarding the energy deliverable on a time basis and to plan an appropriate time of low energy generation time for taking up the WTG maintenance activities ,a meaningful prediction about the power generation of the WTG is needed. This can be achieved by doing data analytics using the internal data from the SCADA (Supervisory Control ad Data Acquisition) system of the WTG and the external data of wind conditions.  This paper deals about the study of the various functional components of the wind turbine which are the source of internal data, a method of data acquisition, data analytics and information generation related to the power generation. Also   data analytics using Machine Learning techniques is done for power prediction and health condition monitoring of WTG. These managerial information are useful for effective Operation, maintenance scheduling, realistic Customer commitment and effectively monitoring the health condition of the WTG.