This report documents implementation of the smart sampling-based probabilistic look-ahead contingency analysis algorithm, the integration with General Electric (GE) Grid Solutions’ commercial energy management system (EMS) tool, and the case study results using real world data from the Bonneville Power Administration (BPA).The probabilistic look-ahead contingency analysis algorithm incorporates forecast errors of renewable energy and load into contingency analysis functions to enable a predictive capability with a more complete picture, revealing the potential violations that are not normally detected by traditional deterministic approaches. To test its performance under practical environments, the probabilistic look-ahead contingency analysis algorithm has been integrated with the dominant GE EMS tool as a proof-of-concept for a seamless integration. To meet the output format of GE EMS tool, an extreme value distribution (EVD) algorithm is newly adapted to analyze the GE EMS’s violation-only output. Real world data from BPA are used to test its performance, and the results clearly show the effectiveness of the developed algorithm and improved situational awareness. This effort is an example of successful technology transition and cooperation under a real-world environment because it is a joint effort from department of energy, a national laboratory, a commercial vendor, and a large utility.