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

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 g...

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Vydáno v:2012 IEEE/ACM Third International Conference on Cyber-Physical Systems s. 129 - 137
Hlavní autoři: Xie, Le, Zhang, Yun, Ilic, Marija D.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Washington, DC, USA IEEE Computer Society 17.04.2012
IEEE
Edice:ACM Conferences
Témata:
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
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Abstract 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).
AbstractList 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).
Author Xie, Le
Ilic, Marija D.
Zhang, Yun
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Keywords spatial aggregation
temporal aggregation
Multi-scale modeling
structure-preserving modeling
data-driven modeling
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SubjectTerms 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
Title Multi-scale Integration of Physics-Based and Data-Driven Models in Power Systems
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