Improved TLBO (teaching-learning-based optimization) algorithm-based hydroelectric generating set PID (proportional-integral-differential) speed regulator parameter optimization

A technology of generator sets and water turbines, which is applied in the directions of hydropower generation, engine functions, engine components, etc., can solve the problems of few parameters and convergence speed, and achieve the effect of optimizing the PID parameters.

Active Publication Date: 2017-06-13
DALIAN UNIV
View PDF7 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Its advantage is that it has fewer parameters and convergence speed, but it is easy to fall into local convergence

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Improved TLBO (teaching-learning-based optimization) algorithm-based hydroelectric generating set PID (proportional-integral-differential) speed regulator parameter optimization
  • Improved TLBO (teaching-learning-based optimization) algorithm-based hydroelectric generating set PID (proportional-integral-differential) speed regulator parameter optimization
  • Improved TLBO (teaching-learning-based optimization) algorithm-based hydroelectric generating set PID (proportional-integral-differential) speed regulator parameter optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0061] The present invention will be further described in conjunction with the specification and specific embodiments.

[0062] Such as figure 1 A parameter optimization of the PID governor of the hydro-generator set based on the improved TLBO algorithm shown includes the following steps:

[0063] 1. Establishment of turbine speed regulation model

[0064] (1) Controller simulation model

[0065] Using PID control, build a parallel PID control simulation model in the turbine speed control system, the controller simulation model is as follows figure 2 shown;

[0066] (2) Simulation model of hydraulic servo system

[0067] The servomotor is controlled by the main pressure distribution valve. It is the most important controlled object in the hydraulic servo system of the entire governor, and it is an integral link in the simulation model. Its physical meaning is that when the main pressure distribution valve is in the middle position, the opening of the servomotor remains u...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention belongs to the technical field of hydroelectric generation, and particularly relates to improved TLBO (teaching-learning-based optimization) algorithm-based hydroelectric generating set PID (proportion-integration-differentiation) speed regulator parameter optimization. The optimization comprises the following steps of (1) building a hydroturbine speed regulating system simulation model; (2) improving a basic TLBO algorithm; (3) applying the improved TLBO algorithm to optimizing parameters of the speed regulator of a hydroturbine speed regulating system, and obtaining a simulation result. Self-adaptive teaching factors, i.e., absorption weight of students and the after-school tutoring of teachers are added into the basic TLBO algorithm, while the convergence speed and the convergence precision are guaranteed, the phenomena of early-maturing and early convergence of the algorithm are avoided. An ITAE index of rotation rate deviation of a hydroturbine set serves as a standard fitness function, and the improved TLBO algorithm is used to optimize the parameters of the speed regulator, so that the convergence speed optimization efficiency is obviously improved, and the phenomenon of local optimum is avoided.

Description

technical field [0001] The invention belongs to the technical field of hydroelectric power generation, and in particular relates to parameter optimization of a PID governor of a hydroelectric generating set based on an improved TLBO algorithm. Background technique [0002] In industrial production and daily life, the safety and stability of using electric energy is an important prerequisite to ensure the safety of our lives and property. Therefore, as the way of providing electric energy, the rated frequency and rated voltage are the parameter standards to ensure the stability and safety of electricity consumption. A hydroelectric power generation system is a system that converts the potential energy of water into electrical energy, and the core is a hydroelectric generator set. The regulating system of the hydro-generator unit uses the hydro-turbine as the regulating device and the hydro-turbine unit as the controlled object. It is a high-order closed-loop control system w...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): F03B15/12
CPCF03B15/12F05B2260/84F05B2270/706Y02E10/20
Inventor 王洪雁裴炳南万瑞文房云飞郑佳
Owner DALIAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap