Big Data Analytic for Cascading Failure Analysis
2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)(2019)
摘要
With the challenges of increased grid dynamics and more variability of power generation from renewable energy sources, rapidly increasing complexity in the grid model, and abundant data from measurements and simulations, the requirements for computational analysis have also increased dramatically. This paper proposes a novel big data analysis approach for power system cascading analysis, prevention, and remediation. The developed techniques will be capable of cascading analysis, better assessment of the systems vulnerability level, as well as proposing potential remediation. Case studies using IEEE 118- bus system and a 563-bus system, with comparisons against a commercial tool, validate the advantages of the developed big data approach: accurate prediction, and more importantly, faster and effective correction actions. The developed techniques could be further used for other power system applications.
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关键词
big data, cascading analysis, corrective action, machine learning
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