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Multi-machine system governor pid parameter optimization method, device, equipment and medium

A multi-machine system and optimization method technology, applied in the field of power systems, can solve the problems of slow particle swarm convergence and low optimization efficiency, achieve good low-frequency oscillation, solve low-frequency oscillation, and high efficiency

Active Publication Date: 2020-09-29
CHINA SOUTHERN POWER GRID COMPANY +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, in the current technology of PID parameter adjustment using the particle swarm optimization algorithm, the convergence speed of the particle swarm is slow, and the optimization efficiency is generally not high.

Method used

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  • Multi-machine system governor pid parameter optimization method, device, equipment and medium
  • Multi-machine system governor pid parameter optimization method, device, equipment and medium
  • Multi-machine system governor pid parameter optimization method, device, equipment and medium

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Embodiment 1

[0057] See figure 1 , figure 1 It is a schematic diagram of the PID parameter optimization device for the multi-machine system governor provided in Embodiment 1 of the present invention, which is used to execute the PID parameter optimization method for the multi-machine system governor provided in the embodiment of the present invention, such as figure 1 As shown, the multi-machine system governor PID parameter optimization device includes: at least one processor 11, such as CPU, at least one network interface 14 or other user interface 13, memory 15, at least one communication bus 12, the communication bus 12 is used for Implement connection communication between these components. Wherein, the user interface 13 may optionally include a USB interface, other standard interfaces, and a wired interface. The network interface 14 may optionally include a Wi-Fi interface and other wireless interfaces. The memory 15 may include a high-speed RAM memory, and may also include a non-...

Embodiment 2

[0067] see figure 2 , a schematic flowchart of a PID parameter optimization method for a multi-machine system governor provided in the second embodiment of the present invention;

[0068] S11. Obtain an initial optimal value range, so as to obtain each particle and a particle group according to the initial optimal value range; wherein, the initial optimal value range is the initial value range of the position vector of each particle;

[0069] It should be noted that the particle swarm optimization algorithm is an optimization algorithm proposed by Kennedy and Eberhart in 1995, inspired by the behavior of birds in search of food. It is another swarm intelligence algorithm after the ant colony algorithm, and finally developed become an effective optimization tool. In the particle swarm optimization algorithm, the potential solution of each optimization problem can be imagined as a point on the d-dimensional search space. These points are called particles, and a total of m part...

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Abstract

The invention discloses a multi-machine system speed governor PID parameter optimization method, comprising the steps of obtaining an initial optimization value range to obtain various particles and aparticle swarm according to the initial optimization value range; for each particle, the position variable of the particle is substituted for the PID parameter of the corresponding unit governor. Thefitness function is obtained according to the weighted sum of the system oscillation damping and the frequency modulation response speed of the generator set under the fault. According to the fitnessfunction, the fitness function value of each particle is obtained, and the fitness function value of the particle is compared with the optimal fitness function value of the particle swarm at the current time. When the fitness function value of the particle is better than the optimal fitness function value of the particle swarm, updating the optimal fitness function value of the particle swarm andthe optimal position of the particle swarm according to the position of the particle; And updating the state of the particles; When the optimal fitness function value of particle swarm satisfies thepreset precision, the optimal PID parameters are obtained. The convergence speed of a particle swarm and the optimization efficiency of the algorithm are improved.

Description

technical field [0001] The invention relates to the technical field of electric power system and automatic control technology, in particular to a PID parameter optimization method, device, equipment and medium of a governor of a multi-machine system. Background technique [0002] In the test of China Southern Power Grid's asynchronous networking system in Yunnan, a long-term, large-amplitude, ultra-low-frequency oscillation with an oscillation period of about 20s occurred for the first time in the power grid. How to ensure the stable operation of this type of power grid needs to be further explored. After asynchronous networking, the load scale of Yunnan power grid is greatly reduced compared with the original synchronous power grid of the Southern Power Grid. Therefore, the frequency response characteristics of Yunnan Power Grid after asynchronization have changed greatly compared with the frequency response characteristics of Southern Power Grid before asynchrony. Effectiv...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/38H02J3/24G06N3/00
CPCG06N3/006H02J3/24H02J3/38
Inventor 周剑甄鸿越徐光虎张建新梅勇刘蔚周挺辉
Owner CHINA SOUTHERN POWER GRID COMPANY
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