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A tuning method of pss parameters in power system based on afsa-bfo algorithm

An AFSA-BFO, power system technology, applied in electrical digital data processing, computing, electrical components, etc., can solve problems such as slow convergence speed, poor adaptive ability, and difficulty in setting rules, so as to improve the speed of convergence, improve Adaptability, the effect of improving the stable operation level

Active Publication Date: 2019-09-13
FUZHOU UNIV
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Problems solved by technology

However, the neural network needs a large number of learning samples and the convergence speed is slow. The search time of the genetic algorithm is too long, and it is easy to converge to the sub-global optimal solution prematurely. However, in fuzzy control, it may have consequences such as poor adaptive ability and difficult rule setting.

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  • A tuning method of pss parameters in power system based on afsa-bfo algorithm
  • A tuning method of pss parameters in power system based on afsa-bfo algorithm
  • A tuning method of pss parameters in power system based on afsa-bfo algorithm

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Embodiment Construction

[0047] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0048] The present invention provides a method for setting PSS parameters of a power system based on the AFSA-BFO algorithm, such as figure 1 shown, including the following steps:

[0049]Step S1: initialization of AFSA and BFO algorithm parameters; in this embodiment, the record dimension is D, the population size is n, the number of iterations is gen, the maximum number of iterations is MAXGEN, the maximum number of attempts is TN, the visual field is Visual, the step size is Step, and congestion degree factor z; the number of chemotaxis Nc of bacteria, the maximum number of steps of one-way movement Ns in the chemotaxis operation, the number of copying operation steps Nre, the number of migration operations Ned, and the migration probability Ped; and randomly generate initialization parameters.

[0050] Step S2: Set gen=1 to perform i...

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Abstract

The invention relates to a power system stabilizer (PSS) parameter setting method based on an AFSA-BFO (Artificial Fish Swarm Algorithm-Bacterial Foraging Optimization) algorithm. Firstly, search is performed by adopting an AFSA; when the adaptability reaches a certain value, the AFSA has been converged to a global optimal area, then the AFSA is switched to a BFO algorithm, and the BFO algorithm will be optimized locally based on the AFSA; and a new judgment mode is introduced by switching the algorithm. A PSS controller set by adopting the AFSA-BFO algorithm has good adjustability on the whole, and the set PSS parameter has good adaptability and still can improve the stable running level of a system under large disturbance.

Description

technical field [0001] The invention relates to the field of power system low-frequency oscillation suppression, in particular to a power system PSS parameter setting method based on the AFSA-BFO algorithm. Background technique [0002] With the rapid growth of the global economy and the rapid increase of population, the use of electric energy in the world is also increasing, so that the load on the power grid is increasing; at the same time, the modern power system has entered the period of large power grids interconnected across regions. Long-distance and large-capacity transmission lines exist widely; these will induce low-frequency oscillations in power systems. If the low-frequency oscillation cannot be suppressed well, it will cause a series of system failures, resulting in large-scale power outages and huge economic losses. In recent years, power system low-frequency oscillation has become one of the key issues affecting the reliable and safe operation of the power g...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/00H02J3/24G06F17/50
CPCG06F30/367H02J3/00H02J3/24H02J2203/20Y02E60/00
Inventor 金涛刘对沈学宇刘页
Owner FUZHOU UNIV
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