Power system stabilizer (PSS) parameter setting method

Abstract

The invention provides a PSS parameter setting method for a power system. The PSS parameter setting method comprises the following steps: (1) initializing AFA and BFO algorithm parameters; (2) letting k = 1, iter = 0, g = h = l = 1; (3) running a corresponding simulation model; (4) using an ITAE criterion as a target function; (5) an AFA-BFO algorithm is adopted to carry out optimization calculation on the target function; (6) executing BFO algorithm operation; (7) the number of iterations iter = iter + 1; (8) judging whether the number of iterations iter reaches the maximum number of iterations gen or not; (9) if the number of iterations iter does not reach the maximum number of iterations gen, turning to the step (7) to continue iteration; (10) if the number of iterations iter reaches the maximum number of iterations gen, outputting the individual extremum and the global extremum; the individual extreme value is the PSS parameter obtained through optimization, and the global extreme value is the objective function value of the power system. According to the technical scheme, the switching mode between the two algorithms can be achieved, and the algorithm convergence speed can be increased under the condition that the convergence precision is guaranteed in the parameter optimization process.

Description

technical field [0001] The invention relates to the technical field of power system low-frequency oscillation suppression, in particular to a power system PSS parameter setting method. Background technique [0002] With the development of my country's interconnected power grid, more and more fast and high-magnification excitation devices are used in the power grid, resulting in weak or negative damping of the power grid. Under external interference, low-frequency oscillations are prone to occur. As an additional damping control for the excitation system, the power system stabilizer (PSS) provides positive damping to the power system, which can suppress low-frequency oscillations and improve the stability of the power system. The parameters of the PSS directly affect the performance of the PSS. If the parameters are not set properly, the performance of the PSS cannot be brought into full play. [0003] PSS tuning methods include phase compensation method, pole configuration ...

AI Technical Summary

Problems solved by technology

For the PSS parameters set by the phase compensation method, only one operating condition is considered, and the robustness cannot meet the requirements when the system is in other operating conditions; the pole allocation method can make the system meet the stability requirements by selecting an appropriate gain matrix , but this method has the problem that the gain matrix is ​​difficult to determine; in recent years, some scholars have introduced intelligent optimization algorithms to tune PSS parameters, such as neural networks, fuzzy control and artificial intelligence algorithms, etc.

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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