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SBIR Phase I: A Robust Real-time Topology Estimator for Power Grids
Phone: (682) 478-8897
Phone: (682) 478-8897
This Small Business Innovation Research (SBIR) Phase I project aims to develop a novel state estimator for power system operations. The research objectives are to develop a commercialized software package of state estimation and conduct testing on different power systems including real systems. This research will use techniques from graph theory, linear algebra, and high dimensional statistics. The novelty of the research is in bringing together cutting-edge ideas from these diverse disciplines to solve the problem of robustness in current state estimators used in power industry. The anticipated technical results include a commercialized software package that largely improves the system monitoring and therefore the operation security of power systems. The broader impact/commercial potential of this project includes 1) the targeted problem (power system state estimator) is extremely critical in modern power grids or smart grids and can help prevent system-wide failures or blackouts if properly handled, 2) the certainty of commercialization of the proposed approach warranting significant NSF support because the provided solution is fast enough for the real-time application and the new state estimator does not ask for additional inputs or requirements comparing with the existing ones, 3) the research team is formed by technical as well as marketing personnel which ensures the success of the sales of the products, 4) the uniqueness of the proposed approach which provides competitive benefits to the market that cannot be met by alternate technologies and can attract further funding from non-SBIR sources and result in direct sales to power industry, 5) the proposed approach develops a unique formulation/solution of state estimation which very possibly leads to further innovations, 6) the new procedure of the proposed approach based on unique formulation and unique philosophy can promote teaching, training and learning in the area of state estimation.
* Information listed above is at the time of submission. *