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TECHNOLOGY LICENSING OPPORTUNITY

LSBmax Algorithm for Boosting Resilience of Electric Grids

A new approach to prevent cascading grid failure through optimized transmission switching (TS) and load shedding

Opportunity: Idaho National Laboratory (INL), managed and operated by Battelle Energy Alliance, LLC (BEA), is offering to enter into a license or collaborative research agreement to commercialize the LSBmax algorithm for boosting the resilience of electric grids. 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 electric power system aims to provide continuous power, but during faults or contingencies, the faulted element is isolated, and power is rerouted, which can result in congestion or violations leading to cascading failures. Load shedding may be needed to avoid these violations and prevent blackouts, which can also be caused by severe weather. Power system resiliency focuses on high impact and low-probability incidents and is boosted by measures such as resilience-based planning, response, and restoration. The work presented focuses on preventive response and addresses the issue of minimizing load shedding after contingencies by using transmission switching.

The LSBmax Algorithm for Boosting the Resilience of Electric Grids Post (N-2) Contingencies [RMB1] is a novel heuristic method that uses a computationally improved algorithm to find the best transmission switching (TS) candidate for reducing load shedding after (N-2) contingencies. The algorithm is designed to find the best TS candidate in a computationally suitable time for practical application. It is faster than the well-known state-of-the-art (i.e., complete enumeration algorithm).

The proposed algorithm lists branches near the load shedding bus with maximum load shedding, so called LSBmax, and eliminates them sequentially. The system is then simulated to verify compliance, and the branch that results in the minimum load shed is the best TS candidate. The algorithm can be used in DC and AC optimal power flow (DCOPF and ACOPF) formulations. The algorithm and software can be applied to any power systems analysis software for rapid implementation[RMB2] [TH3] .

Benefits:

• Reduces load shedding in electric grids after element failures


• Enhances the operational resilience of power systems by rapidly recovering load shedding after cyber-attacks or natural disasters.


• Faster than the state-of-the-art complete enumeration algorithm


• Load shed reduction achieved is comparable to the state-of-the-art

• Parallelization of the proposed algorithm improves computational performance

Target Audience:

• Power systems analysis software companies and power utilities looking to enhance the resilience of their grids and reduce load shedding in the event of contingencies


• Also suitable for researchers and engineers working in power systems and grid resilience.

Development Status: TRL 3: technology has been demonstrated in a laboratory environment. [RMB4]

IP Status: Provisional Patent Application No. 63/375,408, “The LSBmax Algorithm for Boosting Resilience of Electric Grids Post (N-2) Contingencies,” BEA Docket No. BA-1345.

Additional Information:

Hussain, T., Alam, S.M.S., Hansen, T.M., Suryanarayanan, S.: The LSBmax algorithm for boosting resilience of electric grids post (N-2) contingencies. J. Eng. 2021, 807– 816 (2021). https://doi.org/10.1049/tje2.12081

INL seeks 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.

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