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SBIR Phase I: A Robust State Estimator For Power Grids

SBIR Phase I: A Robust State Estimator For Power Grids
SBIR 第一阶段:稳健的电网状态估计器
批准号:
1519498
负责人:
Bei Gou
金额:
$15.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-07-01 至 2016-06-30

项目摘要

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中文摘要
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英文摘要
The broader impact/commercial potential of this project includes 1) the targeted problem (robustness of state estimator) is extremely critical in modern power grids and the proposed approach can help prevent system-wide failures or blackouts if applied, 2) the new state estimation technology is novel in statistics and could be applied in other areas besides power engineering, 3) the research team is formed by technical as well as marketing experts which ensures the success of the development and sales of the products, 4) the competitive market benefits of our products 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 unique formulation/solution of our new state estimation will lead to further innovations and bring a new era of energy management system (EMS) to power grids, 6) the new procedure of the proposed approach based on unique philosophy can promote teaching, training and learning in the area of state estimation.This Small Business Innovation Research (SBIR) Phase I project aims to develop a novel robust state estimator for power system operations, from a revolutionary state estimation technology which was invented in 2009 and patented at Smart Electric Grid, LLC in 2014. The research objective is to solve the robustness problems suffered by the existing state estimators, i.e., no convergence warranty and weakness in detecting multiple bad data, especially topology errors. The invention consists of a new formulation of state estimator and an efficient solving process. The novelty of the research is in bringing together cutting-edge ideas from diverse disciplines including graph theory, linear algebra, matrix theory and high dimensional statistics, to solve the robustness problem of current state estimators. The anticipated technical results include comprehensive testing on different power systems including real systems, and a commercialization plan of the patented technology.
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