Abstract
Parallel computing helped speed up many tasks that can be done independently. The advance in gaming industry did not produce a technology that helps the power industry to reduce the computation time for dynamic simulation in individual cases. To perform faster than real-time simulation for the purpose of predicting power system dynamic trajectory, power industry continues to struggle to reduce the system size and simulation time of large-scale power systems while keeping its dynamic behavior under various disturbances. There is also an acute need for real-time dynamic model reduction as more renewables enter the generation mix with dramatic changes in the generation outputs. All existing model reduction solutions are based on having access to a detailed dynamic model of the system. The system changes by the minutes, dynamic models are only updated annually. To solve this problem, wide-area measurements obtained by the phasor measurement unit (PMU) at the boundaries between the reduced system and the study system is used to represent the external area. An artificial neuro-fuzzy inference system (ANFIS) is established to perform the mapping of the measurement to the external equivalent model. Here the external area is regarded as a black-box. Model reduction studies are conducted on the Northeast Power Coordinating Council (NPCC) under various types of contingencies, by using a co-simulation approach between PSS/E and MATLAB. The results look very promising and will be discussed in this paper.
Original language | English |
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Title of host publication | 2020 American Control Conference, ACC 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 3164-3169 |
Number of pages | 6 |
ISBN (Electronic) | 9781538682661 |
DOIs | |
State | Published - Jul 2020 |
Event | 2020 American Control Conference, ACC 2020 - Denver, United States Duration: Jul 1 2020 → Jul 3 2020 |
Publication series
Name | Proceedings of the American Control Conference |
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Volume | 2020-July |
ISSN (Print) | 0743-1619 |
Conference
Conference | 2020 American Control Conference, ACC 2020 |
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Country/Territory | United States |
City | Denver |
Period | 07/1/20 → 07/3/20 |
Funding
This work was supported by the Engineering Research Center Program of the National Science Foundation (NSF) and Department of Energy (DOE) under NSF Award Number EEC-1041877 and the CURENT Industry Partnership Program. Corresponding to: Zhihao Jiang ([email protected])
Keywords
- Dynamic equivalent
- artificial neuro-fuzzy inference system
- model reduction
- system identification