Modeling a Pneumatic Turbine Speed Control System

1995 ◽  
Vol 122 (1) ◽  
pp. 222-225 ◽  
Author(s):  
Eric R. Upchurch ◽  
Hung V. Vu
Keyword(s):  
Control System ◽  
Speed Control ◽  
Speed Control System ◽  
Turbine Speed

[S0022-0434(00)01001-7]

Research on the Hydropower Frequency Control Strategy for Power Delivery Grid Splitting

2013 ◽  
Vol 392 ◽  
pp. 641-645 ◽  
Author(s):  
Li Meng ◽  
Hao Wang ◽  
Jian She Tian
Keyword(s):  
Control System ◽  
Frequency Control ◽  
Power Grid ◽  
Speed Control ◽  
Power Delivery ◽  
Area Measurement ◽  
Frequency Regulation ◽  
Improvement Program ◽  
Speed Control System ◽  
Turbine Speed

After power delivery grid splitting off from the main power grid, there is the risk of over frequency generator tripping leading to low frequency load shedding action. Regulation characteristic of hydro-turbine speed control system for regional power grid is analyzed by using the measured parameters of hydropower. The turbine speed control effect is analyzed without lower limit of primary frequency regulation. Frequency control improvement program of hydropower generating units in isolated power system is proposed based on wide area measurement system. The scheme uses WAMS to collect power information as governor PID output lead, and to calculate power target into the speed control system.

Turbine speed control system based on a fuzzy-PID

2008 ◽  
Vol 7 (4) ◽  
pp. 268-272 ◽  
Author(s):  
Jian-hua Sun ◽  
Wei Wang ◽  
Hai-yan Yu
Keyword(s):  
Control System ◽  
Speed Control ◽  
Fuzzy Pid ◽  
Speed Control System ◽  
Turbine Speed

The Modeling of Steam Turbine Speed Control System Based on Radial Basis Function Neural Network

2010 ◽  
Vol 139-141 ◽  
pp. 1822-1826
Author(s):  
Yong Ren ◽  
Tao Yang ◽  
Wei Gao ◽  
Yang Hai Li
Keyword(s):  
Neural Network ◽  
Control System ◽  
Radial Basis Function ◽  
Basis Function ◽  
Speed Control ◽  
Power System Stability ◽  
System Stability ◽  
Stability Studies ◽  
Speed Control System ◽  
Turbine Speed

The model of speed control system plays an important role in power system stability studies, the non-linear properties prevent us from getting accurate mechanism model. In this paper, the radial basis function neural network with self-structuring and fast convergence is used in the modeling of steam turbine speed control system in the modeling process, also, this paper presents a method which combines particle swarm optimization algorithm and least-squares algorithm for the neural network’s training, it has the property of high accuracy and fast convergence, after training, the proposed model and related training algorithm are verified by the test data of one power plant, it has proved that the neural network can be used in the modeling of the speed control system for the power system stability studies.

Digital DC Speed Control System in Mine Hoist Application

2011 ◽  
Vol 219-220 ◽  
pp. 1017-1021
Author(s):  
Rui He ◽  
Yun Ping Ge
Keyword(s):  
Control System ◽  
Closed Loop ◽  
Speed Control ◽  
Closed Loop System ◽  
Pi Regulator ◽  
Control Precision ◽  
Speed Control System ◽  
Digital Trigger ◽  
Mine Hoist ◽  
Work Stability

Mine hoist shoulder important transport tasks. Through the analysis of the main circuit of mine hoist, this paper studies out ASCS digital DC speed control system whose core is microprocessor and whose hardware part constitutes digital trigger and double closed loop system. The software part not only achieves the system's digital PI regulator, logic switching, digital trigger phase shift, pulse channel selection and pulse width setting, but also realizes the systematic detection, monitoring, fault diagnosis, which improves the control precision and work stability of the system.

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