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TECHNOLOGY LICENSING OPPORTUNITY Faster Line Switching Algorithm in Electrical Grids A unique and fast bi-level algorithm which succeeds in eliminating post contingency violations with optimal load sh... TECHNOLOGY LICENSING OPPORTUNITY Faster Line Switching Algorithm in Electrical Grids A unique and fast bi-level algorithm which succeeds in eliminating post contingency violations with optimal load shedding in electrical grids. Opportunity: Idaho National Laboratory (INL), managed and operated by Battelle Energy Alliance, LLC (BEA), and Colorado State University are offering the opportunity to enter into a license and/or collaborative research agreement to commercialize this faster line switching algorithm. This technology transfer opportunity is part of a dedicated effort to convert government-funded research into job opportunities, businesses and ultimately an improved way of life for the American people. Overview: The electrical grid is becoming more complex, dynamic, and less predictable due to the integration of newer technologies and approaches, driven jointly by science and policy. The reducing inertia and increasingly dynamic grid have increased the risk of cascading failures, thereby compromising resiliency. Two major challenges of the future grid are prediction and mitigation of cascading failures, and real-time (RT) adaptive methods for the protection of remedial action schemes (RAS). RAS is a procedure that activates under certain system stress conditions that can exceed the individual component protection threshold. The development of practical solutions for dynamic reconfiguration requires faster than RT (FTRT) predictive capabilities to analyze thousands of scenarios every few microseconds. The FTRT scheme has yet to be solved as it requires a highly efficient and accurate search algorithm for transmission switching, which would mitigate cascading failure. Description: The aim of electrical power systems is to provide continuous power to its customers. But, in the case of a generator or line contingency, load shedding may be the only solution to avoid post contingency violations (PCVs). Lack of proper load shedding may lead to cascading failures. Research in the past has minimized the amount of load shedding as much as possible while preventing PCVs, to mitigate cascading failures without transmission switching (TS). TS, however, provides topology changes and is beneficial for contingency analysis, but is often computationally too complex to implement. An AC-based real-time contingency analysis (RTCA) tool, utilizing TS, and capable of handling large-scale real power systems was developed to overcome these challenges. Three heuristic methods were proposed using the RTCA tool and implemented on large-scale power systems. Although the RTCA tool was computationally less complex, success rates to completely remove PCVs were only between 10% -30%, and ultimately did not completely prevent cascading failures. Thus, there is a need to improve the existing TS algorithms to mitigate cascading failures. Benefits: Faster bi-level algorithm, with manageable computational complexity Speed-ups averaged 18 times faster Accuracy averaged between 97.3-99.17% Applications: Power systems Power systems analysis software Independent power systems operators Electric utilities Energy management companies Development Status: TRL 1. Early-Stage Concept IP Status: Patent Application No. US/2021/026540, “Hybridized Transmission Switching for Load Shed Recovery (LSR),” BEA Docket No. BA-1206. INL is seeking to license the above intellectual property to a company with a demonstrated ability to bring such inventions to the market. Exclusive rights in defined fields of use may be available. Added value is placed on relationships with small businesses, start-up companies, and general entrepreneurship opportunities. Please visit Technology Deployment’s website at https://inl.gov/inl-initiatives/technology-deployment for more information on working with INL and the industrial partnering and technology transfer process. Companies interested in learning more about this licensing opportunity should contact Andrew Rankin at td@inl.gov.