Risk control assistant decision-making method and system based on artificial intelligence learning

A risk control and auxiliary decision-making technology, applied in the direction of instruments, AC network circuits, electrical components, etc., can solve the problems of reducing the safety and stability of power grid operation, overloading, and accident rate increase, so as to reduce the probability and impact of system risk range effect

Inactive Publication Date: 2020-07-10
GUIZHOU POWER GRID CO LTD
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

In this case, the accident rate of the system is also relatively increased, and the losses caused are also incalculable.
Especially in the application of regional power grids, due to the slow update and inadequate protection measures of some equipment, heavy load or even overload often occurs, which reduces the safety and stability of power grid operation and brings certain problems to the maintenance of normal power supply of the power grid. Difficulties

Method used

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  • Risk control assistant decision-making method and system based on artificial intelligence learning
  • Risk control assistant decision-making method and system based on artificial intelligence learning
  • Risk control assistant decision-making method and system based on artificial intelligence learning

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Embodiment 1

[0042] With the rapid development of the power grid, higher requirements have been put forward for safe and reliable power supply. Facing the new situation of severe shortage of power supply, prominent contradictions in the stability of large cross-regional power grids, and frequent operation of regional power, coupled with a series of domestic and foreign events in recent years A series of large-scale power outages in the power grid has promoted the safety of the power grid to the strategic level of national security and social stability, and has attracted great attention from all aspects. The characteristics and development trends of accidents, combined with artificial intelligence learning strategies, can realize the pre-control of power grid operation risks.

[0043] refer to Figure 1 to Figure 5 , Figure 8 , Figure 9 , which is the first embodiment of the present invention, provides a risk control auxiliary decision-making method based on artificial intelligence lear...

Embodiment 2

[0102] refer to Figure 6 , Figure 7 and Figure 10 , is the second embodiment of the present invention. This embodiment is different from the first embodiment in that it provides a risk control auxiliary decision-making system based on artificial intelligence learning, including a master control module 100 for constructing risk control model.

[0103] The server module 200 is used to establish a framework for regional power grid risk assessment and auxiliary decision-making based on SCADA real-time data.

[0104] The input management module 300 is used to manage and run all parameters in the system and define fault sets.

[0105] The analysis module 400 is used to calculate and process the grid parameters input into the management module 300, obtain risk indicators, and formulate risk control strategies corresponding to the risk indicators.

[0106] The output management module 500 is used to graphically process the input data, store the processing results of risk indica...

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Abstract

The invention discloses a risk control assistant decision-making method and system based on artificial learning, and the method comprises the steps that a main control module builds an operation riskcontrol model through employing a risk control strategy; a server module constructs a set of regional power grid risk assessment and auxiliary decision-making framework based on SCADA real-time data by using the risk control model, and generates a power grid operation risk index; and a framework uses the risk control model to calculate, evaluate and analyze the power grid operation risk indexes, constructs a corresponding risk pre-control scheme and generates a risk pre-control auxiliary decision. According to the invention, a regional power grid operation risk index system is determined; an optimal load reduction and network reconstruction operation risk method is adopted to reduce the risk occurrence probability and influence range of the system; and a set of regional power grid risk assessment and assistant decision-making system based on SCADA real-time data is developed to effectively assess and research the fault occurrence probability and consequence, thereby providing effectivedecision-making support for preventing operation accidents.

Description

technical field [0001] The invention relates to the technical field of power grid risk control, in particular to an artificial intelligence learning-based risk control auxiliary decision-making method and system. Background technique [0002] With the rapid development of social life and production, the operation and application of power systems have become more and more complex and unstable. In this case, the accident rate of the system is also relatively increased, and the losses caused are also incalculable. Especially in the application of regional power grids, due to the slow update and inadequate protection measures of some equipment, heavy load or even overload often occurs, which reduces the safety and stability of power grid operation and brings certain problems to the maintenance of normal power supply of the power grid. Difficulties. [0003] The present invention introduces the application of risk theory to the safe operation evaluation of the power grid, focus...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06H02J3/00
CPCG06Q10/0635G06Q50/06H02J3/00
Inventor 罗艳王庭刚周智海肖辅盛高浩张诗琪何立新卞苏波蒋琳延敏娜粟景
Owner GUIZHOU POWER GRID CO LTD
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