Distribution Systems Operations in the age of Big Data
* 21PESGM2725, Advanced Distribution Management System in the age of Big Data: X. WANG, GE Digital * 21PESGM2726, Lessons learned from DER integration and DMS at SDG&,E: L. ABCEDE, San Diego Gas and Electric * 21PESGM2727, Data-driven Outage management and restoration: Z. WANG, Iowa State * 21PESGM2728, Data-driven modeling and control of power distribution systems: N. YU, UCR * 21PESGM2729, ADMS traffic flow analysis: anomaly detection: A. DUBEY, Washington State University
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PES
IEEE Members: $10.00
Non-members: $20.00
Rapidly evolving electric power distribution systems call for advanced methods to control and coordinate their operations for improved operational efficiency and resilience. Fortunately, the grid modernization efforts have resulted in the proliferation of information and communication technologies for monitoring and control of the distribution grid. These devices range from the installations of remote terminal units and switches on the primary feeders to rapidly increasing penetrations of secondary level devices such as micro-PMUs, smart inverters, and smart meters. The availability of data brings new opportunities and challenges to managing the distribution grid. For example, while secondary measurements provide the much-needed visibility on the secondary feeders, they also increase the vulnerabilities with respect to cyberintrusions and false-data injections. This panel brings together experts to discuss how distribution systems operations are evolving in the age of big data. Specifically, the talks will address the innovations that allow using bigdata to improve the efficiency, reliability, and resilience of the distribution system. Further, the panelists will explore the techniques to manage data flow and identify anomalous measurements. The panel will conclude with real-world industry-driven cases of using bigdata for distribution systems operations and relevant challenges.
Chairs:
Anamika Dubey, Washington State University, Nanpeng Yu, UCR
Sponsor Committees:
(AMPS) Big Data Analytics