AC-DC large power grid dynamic security risk situation rolling prospective early warning method and system

A technology of dynamic safety and large power grid, applied in the direction of emergency treatment AC circuit layout, general control system, neural learning method, etc., can solve the problem that the calculation speed of the early warning method is difficult to meet the rapidity requirements of online applications, and is not included, and achieves a comprehensive reflection. , the effect of increasing the rationality and clarifying the significance of the project

Active Publication Date: 2020-06-19
SHANDONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the inventors found that the existing early warning methods based on control costs have at least the following deficiencies: (1) HVDC power modulation is one of the important control measures in the AC / DC hybrid power grid, but it is not included in the existing early warning classification strategies. measure
(2) After considering the dynamic security constraints, the calculation speed of the existing early warning methods is difficult to meet the rapidity requirements of online applications
(3) According to the satisfaction of safety constraints, the operating state of the power system is divided into various categories such as normal safe state, normal unsafe state, and emergency state. The existing early warning classification results cannot reflect this information

Method used

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  • AC-DC large power grid dynamic security risk situation rolling prospective early warning method and system
  • AC-DC large power grid dynamic security risk situation rolling prospective early warning method and system
  • AC-DC large power grid dynamic security risk situation rolling prospective early warning method and system

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Embodiment 1

[0033] Such as figure 1 As shown, this embodiment provides a rolling forward-looking early warning method for the dynamic security risk situation of the AC / DC power grid, including:

[0034] S1: Use stacked denoising autoencoders and extreme learning machines to build a TTC rapid evaluation model, and use the training sample set to train the TTC rapid evaluation model;

[0035] S2: According to the obtained prediction information of grid load power and new energy output, generate future state operation scenarios;

[0036] S3: According to the trained TTC rapid assessment model, combined with the heuristic search method, calculate the type of preventive control measures required to meet the ATC margin constraints;

[0037] S4: According to the type of operation state and the type of prevention and control measures in which the power grid is located, perform hierarchical early warning for future state operation scenarios;

[0038] S5: Scroll to obtain the latest forecast infor...

Embodiment 2

[0094] Such as Figure 6 As shown, this embodiment provides a rolling forward-looking early warning system for the dynamic security risk situation of the AC / DC power grid, including:

[0095] The TTC rapid evaluation model building module is configured to use a stacked noise reduction autoencoder and an extreme learning machine to construct a TTC rapid evaluation model, and use the training sample set to train the TTC rapid evaluation model;

[0096] The control cost calculation module is configured to calculate the type of preventive control measures required to meet the ATC margin constraints according to the trained TTC fast assessment model, combined with a heuristic search method;

[0097] The warning grading module is configured to perform hierarchical and grading warnings for future state operation scenarios according to the type of operation state and the type of prevention and control measures in which the power grid is located.

[0098] The early warning result roll...

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Abstract

The invention discloses an AC-DC large power grid dynamic safety risk situation rolling prospective early warning method and system. The method comprises the steps: constructing an original feature set of a TTC rapid evaluation model; generating a training sample set of a TTC rapid evaluation model based on the power grid topological structure and the prediction information in a future period of time; establishing a TTC rapid evaluation model based on SDAE and ELM; generating a future state operation scene, and based on a TTC rapid evaluation model and a heuristic search method, calculating aprevention and control measure type required for ensuring system safety; and carrying out layered and graded early warning on the operation scene according to the operation state category of the powergrid and the required prevention and control measure type. Based on the deep learning technology, rolling early warning of the dynamic security risk situation can be rapidly carried out, the final layered and graded early warning result can reflect the security of the system operation state more comprehensively, and effective guidance information can be provided for the next prevention and control decision.

Description

technical field [0001] The present disclosure belongs to the field of dynamic security risk early warning of electric power system, and in particular relates to a rolling forward-looking early warning method and system for dynamic security risk situation of AC / DC large power grid. Background technique [0002] With the application of large-capacity HVDC transmission technology, the modern power system has become an AC-DC hybrid power grid. A local short-circuit fault in the AC system may cause continuous commutation failure or blockage of HVDC, which will cause large-scale power flow transfer and huge power shortage in the AC system, and destroy the safety of the entire system. The forward-looking and early warning of security risk situation is one of the key technologies to ensure the safe operation of the power grid. It can conduct dynamic security analysis on possible future operation scenarios in advance and identify high-risk operation scenarios, reserve sufficient time...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06F30/20
CPCG06Q10/04G06Q10/0635G06Q50/06Y04S10/50H02J2203/10H02J3/001G05B19/0428G05B2219/2639G06N3/088
Inventor 刘玉田闫炯程李常刚
Owner SHANDONG UNIV
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