Attachment A Performance Work Statement Data Analytics

Summary
Implement a data analytic system (software/platforms/models) that can reduce and prevent failures and guide maintenance events in. With the many data streams that the Bureau of Reclamation (Reclamation) powerplants already collect from various power generation equipment, Reclamation is seeking to identify and monitor useful relationships between multiple data streams to identify signals of deterioration, impending failures, or other operational issues, as well as to identify likely preventative actions when anomalies occur. To do this, Reclamation is seeking an Artificial Intelligence (AI)/Machine Learning (ML) data analysis software/platform to implement. The system will be evaluated as a pilot project for the first year using data from 4 units at a hydro powerplant. Upon successful conclusion, and at Reclamation discretion, the software/platform will be fully deployed within Reclamation’s on-premise virtualized infrastructure and integrated with Reclamation’s historian located within this same environment. Deployment will initially start with 4 units and then be expanded in steps in successive years to cover additional Reclamation powerplants.

Background & Introduction
Reclamation is a water management agency in the 17 western states. We are known best for construction of dams, powerplants, and canals, including Hoover Dam on the Colorado River, Grand Coulee Dam on the Columbia River, and Folsom Dam on the American River. Reclamation is the largest wholesaler of water in the country and second largest producer of hydroelectric power in the western United States. Reclamation is organized into five regions (Missouri Basin and Arkansas-Rio Grande-Texas Gulf [MB], Lower Colorado Basin [LCB], California-Great Basin Region [CGB], Columbia-Pacific Northwest [CPN], and Upper Colorado Basin [UCB]). As equipment continues to age in the Reclamation infrastructure, a means to predict and prevent failure is at the forefront of operations and maintenance. One of the best economical means to accomplish this is through data anomaly detection and predictive maintenance for power generation applications. Reclamation would like to initially pilot a data analysis solution (software/platforms/models) that can predict and prevent failures and guide maintenance activities in hydroelectric power generation plants. With the many data streams already being collect from various power generation equipment and stored in a centralized historian, Reclamation is seeking to identify and monitor useful relationships between multiple data streams to identify signals of deterioration, impending failures, or other operational issues, as well as to identify likely preventative actions when anomalies occur. To do this, Reclamation intends to implement an Artificial Intelligence (AI)/Machine Learning (ML) data analysis system and platforms via a pilot project. Reclamation is seeking a proven, commercial-off-the-shelf (COTS) solution that includes software licenses, training, technical, system administration, end-users, and patch/updates support.