Application of improved BP neural network based on LM algorithm in desulfurization system of thermal power plant

2017 ◽  
Author(s):  
Huanxin Cheng ◽  
Lijie Cui ◽  
Jing Li
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Bp Neural Network ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Lm Algorithm

Review of Control Strategies Employing Neural Network for Main Steam Temperature Control in Thermal Power Plant

2014 ◽  
Vol 66 (2) ◽  
Author(s):  
N. A. Mazalan ◽  
A. A. Malek ◽  
Mazlan A. Wahid ◽  
M. Mailah
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Temperature Control ◽  
Pid Control ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Heat Rate ◽  
Steam Temperature ◽  
Multiple Variables ◽  
Main Steam

Main steam temperature control in thermal power plant has been a popular research subject for the past 10 years. The complexity of main steam temperature behavior which depends on multiple variables makes it one of the most challenging variables to control in thermal power plant. Furthermore, the successful control of main steam temperature ensures stable plant operation. Several studies found that excessive main steam temperature resulted overheating of boiler tubes and low main steam temperature reduce the plant heat rate and causes disturbance in other parameters. Most of the studies agrees that main steam temperature should be controlled within ±5 Deg C. Major factors that influenced the main steam temperature are load demand, main steam flow and combustion air flow. Most of the proposed solution embedded to the existing cascade PID control in order not to disturb the plant control too much. Neural network controls remains to be one of the most popular algorithm used to control main steam temperature to replace ever reliable but not so intelligent conventional PID control. Self-learning nature of neural network mean the load on the control engineer re-tuning work will be reduced. However the challenges remain for the researchers to prove that the algorithm can be practically implemented in industrial boiler control.

Study on Thermal Power Plant Safety Evaluation Based on BP Neural Network

2014 ◽  
Vol 687-691 ◽  
pp. 2083-2086
Author(s):  
Chao Wang ◽  
Ying Jie Lian
Keyword(s):  
Neural Network ◽  
Power Generation ◽  
Power Plant ◽  
Bp Neural Network ◽  
Thermal Power ◽  
Safety Evaluation ◽  
Electric Power Industry ◽  
Plant Production ◽  
Plant Safety ◽  
Safety Production

Electric power industry is a basic industry of national economy, the power plant production safety related to people's life safety and property of the state, the power of reform and social stability, safety evaluation of power generation enterprises is an important guarantee of safety production in power generation enterprises.The paper establishes the BP neural network model, utilize BP neural network optimization ability and good fitting ability, combining the index system build, carries on the appraisal to the power generation enterprise security.Now the instance verification results show that BP neural network is applied in safety evaluation of power generation enterprises, not only can accurately evaluate the safety situation of power generation enterprises, and the speed of convergence process is quickly.

Recurent Neural Network as a Tool for Parameter Anomaly Detection in Thermal Power Plant

2015 ◽  
Vol 6 (8) ◽  
pp. 448-455 ◽  
Author(s):  
A. Hajdarevic ◽  
L. Banjanovic-Mehmedovic ◽  
I. Dzananovic ◽  
F. Mehmedovic ◽  
M. Ayaz Ahmad
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Anomaly Detection ◽  
Thermal Power Plant ◽  
Thermal Power
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