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Fault recovery method of distribution network based on self-learning mechanism

A technology of distribution network failure and recovery method, which is applied in the direction of automatic disconnection emergency protection devices, electrical components, circuit devices, etc., and can solve problems such as slow speed and poor performance of the scheme

Active Publication Date: 2022-07-08
STATE GRID HENAN ELECTRIC POWER COMPANY ZHENGZHOU POWER SUPPLY +2
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is: to overcome the deficiencies of the existing technology, to provide a method that can solve the defects of slow speed and poor performance of the traditional online decision-making method, and can effectively use the processing experience of expected accidents and similar historical faults to propose A distribution network fault recovery method based on self-learning mechanism

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  • Fault recovery method of distribution network based on self-learning mechanism
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  • Fault recovery method of distribution network based on self-learning mechanism

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Embodiment Construction

[0040] Attached below figure 1 , figure 2 , image 3 The present invention is further explained and illustrated with specific embodiments:

[0041] A distribution network fault recovery method based on a self-learning mechanism, comprising the following steps:

[0042] Step 1: Build a self-learning database; when the distribution network is in normal operation, the expected accident set is reasonably formulated according to the risk assessment results, and the expected accident simulation is carried out for high-risk equipment and locations in order of risk from high to low, so as to build a system based on A self-learning database of anticipated accident simulation and historical fault handling schemes, so that the power transfer scheme of similar faults can be directly utilized after a fault;

[0043] Step 2: Evaluation and matching of similar fault states; after the fault, extract the current network fault characteristics, and sequentially calculate the network topology...

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Abstract

The invention discloses a fault recovery method for a distribution network based on a self-learning mechanism. When the power grid is in normal operation, an expected accident simulation is performed according to a risk assessment result, and a self-learning database based on an accident plan and a historical fault recovery scheme is constructed; The fault features are extracted, and the similarity between the current fault and the fault stored in the database is calculated, and the order is sorted from high to low; the task of power supply recovery is quickly and reliably realized by using a power supply recovery scheme that matches similar faults. The invention transforms the traditional complex and time-consuming online optimization problem into the similarity evaluation problem of limited fault state, which greatly reduces the real-time calculation amount while ensuring the quality of the fault recovery scheme, thereby improving the power supply recovery decision-making speed and scheme performance. Upgrade the power supply recovery system to an intelligent control system with self-learning, self-improvement and continuous evolution capabilities.

Description

technical field [0001] The invention relates to a distribution network fault recovery method based on a self-learning mechanism, belonging to the field of power system automation and distribution network fault recovery. Background technique [0002] The distribution network in the power system undertakes the important task of distributing electric energy to thousands of households, which directly affects the power supply reliability and power quality of power users. The reliability of power supply has been widely valued. As the core function of self-healing control of intelligent distribution network, power supply recovery is of great significance to improve the reliability of power grid power supply. [0003] The power supply restoration of the distribution network needs to consider factors such as power loss load, switching operations, load balance, voltage quality and network loss. It is a multi-objective multi-constraint nonlinear combinatorial optimization problem. The...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02H7/26H02H3/06
CPCH02H7/262H02H3/066Y04S10/52
Inventor 鲍薇辛忠良燕跃豪孔汉杰赵乔董文娜王增平
Owner STATE GRID HENAN ELECTRIC POWER COMPANY ZHENGZHOU POWER SUPPLY
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