Wind Farms generate humongous volumes of structured and unstructured WTG data, which is stored in various systems such as SCADA, SAP, File System, etc., For instance, SCADA data provides parameters such as condition, health, controlling, and performance of each turbine. These parameters obtained from SCADA data helps in understanding power output, operational performance, health and maintenance condition of each turbine. Depending on such variety of parameters, WTG can raise an alarm in case of any error, which includes mechanical part failure, generator malfunction, gear box failure, etc.
Upon receiving an alarm, the Wind farm operations team needs to fetch data related to faulty Wind turbine, location, material stock availability, relevant technical repair instructions etc., to understand and address the error immediately. As the information is stored in multiple systems, it was difficult for the site engineer to fetch and act instantly. Also, to collect and verify the ‘Preventive Maintenance’ & ‘Non-Compliance’ reports involved high latency, huge time and efforts.
Due to unavailability of meaningful & intelligent data instantly, the decision to mitigate the risk after receiving a warning sometimes went haywire. To invest efforts in gathering the unstructured & structured data, organizing it and then utilizing it to support the decision science was a big problem. Thus, the client wanted an intelligent, high-performance data management platform that would allow storing and ingestion of different kinds of data i.e., structured and unstructured data. The platform would help site engineers in faster decision making through data driven intelligence. It would equip site engineers with data intelligence of multidimensional insights in a single unified dashboard view.