Optimization method of hydraulic turbine speed regulation system based on BP-FOA hybrid algorithm

Abstract

The invention discloses an optimization method of a hydraulic turbine speed regulation system based on a BP-FOA hybrid algorithm, which includes the following steps: the parameters of a hydraulic turbine speed regulation system are collected, and a model of the hydraulic turbine speed regulation system is established; regulation parameters kp, ki and kd are optimized by using a fruit fly optimization algorithm; optimization solution is carried out for the optimized regulation parameters kp, ki and kd based on the deep search characteristic of a BP neural network; and finally, whether optimal parameters are output when an optimized performance indicator reaches the maximum number of iterations is judged, the process is ended if the optimal parameters are output, and the method returns if the optimal parameters are not output. The convergence accuracy is enhanced while the hydraulic turbine speed regulation system is avoided trapping into the local optimum. The optimization is more comprehensive and reasonable. The method has the characteristics of multiple POPID adjustment parameters and high adjustment accuracy.

Description

technical field [0001] The invention relates to the technical field of optimization of a water turbine speed control system, in particular to a method for optimizing a water turbine speed control system based on a BP-FOA hybrid algorithm. Background technique [0002] The control structure of the traditional hydraulic turbine speed control system generally adopts parallel PID control, which has the advantages of simple and easy operation. With the development of the power system, the stability requirements of the hydroelectric unit are also increasing. There are many problems such as poor stability when the system load fluctuates, and insufficient self-regulation ability in the face of emergencies in the power system. Facing the shortcomings of the traditional classic water turbine speed control system, a large number of scholars have proposed advanced intelligent control methods, such as fuzzy PID control, BP neural network control, chaotic particle swarm control, etc. Thes...

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Problems solved by technology

[0002] The control structure of the traditional hydraulic turbine speed control system generally adopts parallel PID control, which has the advantages of simple and easy operation. With the development of the power system, the stability requirements of the hydroelectric unit are also increasing. Poor stability when the system load fluctuates, insufficient self-regulation ability in the face of emergencies in the power system, and many other problems

Facing the shortcomings of the traditional classic water turbine speed control system, a large number of scholars have proposed advanced intelligent control methods, such as fuzzy PID control, BP neural network control, chaotic particle swarm control, etc. These studies further optimize the water turbine speed control system, making the water turbine The speed regulation performance has been significantly improved, but there are still deficiencies in responding to system requirements and reducing the impact on the power system.

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