Multi-scale Integration of Physics-Based and Data-Driven Models in Power Systems

• Published in: 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems pp. 129 - 137
• Main Authors: Xie, Le, Zhang, Yun, Ilic, Marija D.
• Format: Conference Proceeding
• Language: English
• Published: Washington, DC, USA IEEE Computer Society 17.04.2012; IEEE
• Series: ACM Conferences
• Subjects: Biological system modeling; Computational modeling; Computing methodologies; Computing methodologies > Modeling and simulation; Computing methodologies > Modeling and simulation > Model development and analysis; Computing methodologies > Modeling and simulation > Model development and analysis > Modeling methodologies; Data models; data-driven modeling; Generators; Load modeling; Mathematical model; Multi-scale modeling; Power system dynamics; spatial aggregation; structure-preserving modeling; temporal aggregation; spatial aggregation; temporal aggregation; Multi-scale modeling; structure-preserving modeling; data-driven modeling
• ISBN: 9780769546957; 0769546951; 1467315370; 9781467315371
• DOI: 10.1109/ICCPS.2012.21

The major subject of this paper is the introduction and testing of a new modeling paradigm necessary for enabling sustainable performance of electric energy systems. In previous work we have identified major challenges to systematically modeling distributed, non-uniform resources emerging in power grids. Today's modeling of electric energy systems is either entirely based on first principles which suffers significantly from the ever-increasing complexity of non-uniform devices, or is purely based on computer science data-driven approaches which lose the fundamental physical insights of electric power networks. Therefore, it is very difficult with today's modeling practices to integrate distributed non-uniform resources using both first-principle and data driven approaches in large-scale cyber-physical energy systems. In sharp contrast, this paper presents a holistic multi-scale modeling approach by combing advances from (1) physics based modeling of emerging distributed resources (e.g. wind generation and storage devices), and (2) data-driven modeling of load resources. With both physics-based models of distributed resources and data-driven models of flexible demands, key parameters are abstracted and identified from the detailed dynamical models necessary for the multi-scale power system operations. The proposed modeling framework is tested using realistic phasor measurement unit data obtained from Electric Reliability Council of Texas (ERCOT).