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A fast emergency control method based on depth feedforward neural network and numerical integration sensitivity

A feedforward neural network, emergency control technology, applied in the direction of AC network circuit, AC network voltage adjustment, power network operating system integration, etc.

Inactive Publication Date: 2018-12-11
ZHEJIANG UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to solve the shortcomings of the existing emergency control algorithm, which has a large amount of calculation and the calculation speed cannot meet the online calculation requirements of the power system in the calculation of the emergency control strategy of the power system, and provides a method based on deep feedforward neural network and numerical integration sensitivity. Rapid Emergency Control Methods

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  • A fast emergency control method based on depth feedforward neural network and numerical integration sensitivity
  • A fast emergency control method based on depth feedforward neural network and numerical integration sensitivity
  • A fast emergency control method based on depth feedforward neural network and numerical integration sensitivity

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Embodiment Construction

[0093] The algorithm proposed by the invention is used for simulation on the IEEE39 system. The training samples of the classification neural network are collected according to the following principles: (1) The output level of the generator, and the load level is randomly generated between 60% and 120%. (2) The combination of a generator output level and load level ensures that the power flow calculation results are reasonable. (3) The fault location setting includes three-phase short-circuit faults at both ends of each line; according to the above conditions, the transient stability analysis is performed to extract the transient stability performance index and the transient stability constraint function value as the input and output values ​​of the neural network for training generation and classification Neural network training sample set. All transient instability samples in the above classification neural network training sample set constitute a fitting neural network tra...

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Abstract

The invention discloses a fast emergency control method based on a depth feedforward neural network and a numerical integral sensitivity. In this method, a two-layer deep feedforward neural network isconstructed, which consists of classification neural network and fitting neural network. Transient stability performance indexes are extracted as input of neural network through short-time numericalintegration. Transient stability evaluation and numerical calculation of transient stability constraint function are carried out through deep feedforward neural network. Combined with numerical integration sensitivity, the gradient and sensitivity of transient stability constraint function with respect to emergency control variables are obtained. Finally, according to the sensitivity of each control variable, the optimal control variable optimization method is used to obtain the final emergency control strategy. The invention converts the numerical integration on the original system into neural network calculation for most of the time, which greatly reduces the calculation amount while retaining the calculation property of the original system transient stability constraint function.

Description

technical field [0001] The invention belongs to power system automation, and relates to a power system emergency control method suitable for online calculation, in particular to a fast emergency control method based on a deep feedforward neural network and numerical integration sensitivity. Background technique [0002] The continuous expansion of the power grid and the emergence of the power market have made the operating environment of the power system more complex, and the requirements for the safe and stable operation of the power grid have become higher and higher. Although there have been quite a lot of research results in the field of stability control system in my country, there are still many deficiencies. The method of "offline calculation and real-time matching" in stability control has a large amount of calculation, and has poor adaptability to changes in operating mode and network structure, and is prone to mismatch; "online pre-decision, real-time matching" mea...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/00H02J3/14
CPCH02J3/00H02J3/14H02J2203/20Y02B70/3225Y04S20/222
Inventor 王建全高一凡肖谭南
Owner ZHEJIANG UNIV
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