A new coordinated control strategy for boiler-turbine system of coal-fired power plant

This paper presents the new development of the boiler-turbine coordinated control strategy using fuzzy reasoning and autotuning techniques. The boiler-turbine system is a very complex process that is a multivariable, nonlinear, slowly time-varying plant with large settling time and a lot of uncertai...

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Veröffentlicht in:IEEE transactions on control systems technology 2005-11, Vol.13 (6), p.943-954
Hauptverfasser: Li, Shaoyuan, Liu, Hongbo, Cai, Wen-Jian, Soh, Yeng-Chai, Xie, Li-Hua
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Liu, Hongbo
Cai, Wen-Jian
Soh, Yeng-Chai
Xie, Li-Hua
description This paper presents the new development of the boiler-turbine coordinated control strategy using fuzzy reasoning and autotuning techniques. The boiler-turbine system is a very complex process that is a multivariable, nonlinear, slowly time-varying plant with large settling time and a lot of uncertainties. As there exist strong couplings between the main steam pressure control loop and the power output control loop in the boiler-turbine unit with large time-delay and uncertainties, automatic coordinated control of the two loops is a very challenging problem. This paper presents a new coordinated control strategy (CCS) which is organized into two levels: a basic control level and a high supervision level. Proportional-integral derivative (PID) type controllers are used in the basic level to perform basic control functions while the decoupling between two control loops can be realized in the high level. A special subclass of fuzzy inference systems, called the Gaussian partition with evenly (GPE) spaced midpoints systems, is used to self-tune the main steam pressure PID controller's parameters online based on the error signal and its first difference, aimed at overcoming the uncertainties due to changing fuel calorific value, machine wear, contamination of the boiler heating surfaces and plant modeling errors. For the large variation of operating condition, a supervisory control level has been developed by autotuning technique. The developed CCS has been implemented in a power plant in China, and satisfactory industrial operation results demonstrate that the proposed control strategy has enhanced the adaptability and robustness of the process. Indeed, better control performance and economic benefit have been achieved.
doi_str_mv 10.1109/TCST.2005.854319
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The boiler-turbine system is a very complex process that is a multivariable, nonlinear, slowly time-varying plant with large settling time and a lot of uncertainties. As there exist strong couplings between the main steam pressure control loop and the power output control loop in the boiler-turbine unit with large time-delay and uncertainties, automatic coordinated control of the two loops is a very challenging problem. This paper presents a new coordinated control strategy (CCS) which is organized into two levels: a basic control level and a high supervision level. Proportional-integral derivative (PID) type controllers are used in the basic level to perform basic control functions while the decoupling between two control loops can be realized in the high level. A special subclass of fuzzy inference systems, called the Gaussian partition with evenly (GPE) spaced midpoints systems, is used to self-tune the main steam pressure PID controller's parameters online based on the error signal and its first difference, aimed at overcoming the uncertainties due to changing fuel calorific value, machine wear, contamination of the boiler heating surfaces and plant modeling errors. For the large variation of operating condition, a supervisory control level has been developed by autotuning technique. The developed CCS has been implemented in a power plant in China, and satisfactory industrial operation results demonstrate that the proposed control strategy has enhanced the adaptability and robustness of the process. 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The boiler-turbine system is a very complex process that is a multivariable, nonlinear, slowly time-varying plant with large settling time and a lot of uncertainties. As there exist strong couplings between the main steam pressure control loop and the power output control loop in the boiler-turbine unit with large time-delay and uncertainties, automatic coordinated control of the two loops is a very challenging problem. This paper presents a new coordinated control strategy (CCS) which is organized into two levels: a basic control level and a high supervision level. Proportional-integral derivative (PID) type controllers are used in the basic level to perform basic control functions while the decoupling between two control loops can be realized in the high level. A special subclass of fuzzy inference systems, called the Gaussian partition with evenly (GPE) spaced midpoints systems, is used to self-tune the main steam pressure PID controller's parameters online based on the error signal and its first difference, aimed at overcoming the uncertainties due to changing fuel calorific value, machine wear, contamination of the boiler heating surfaces and plant modeling errors. For the large variation of operating condition, a supervisory control level has been developed by autotuning technique. The developed CCS has been implemented in a power plant in China, and satisfactory industrial operation results demonstrate that the proposed control strategy has enhanced the adaptability and robustness of the process. 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The boiler-turbine system is a very complex process that is a multivariable, nonlinear, slowly time-varying plant with large settling time and a lot of uncertainties. As there exist strong couplings between the main steam pressure control loop and the power output control loop in the boiler-turbine unit with large time-delay and uncertainties, automatic coordinated control of the two loops is a very challenging problem. This paper presents a new coordinated control strategy (CCS) which is organized into two levels: a basic control level and a high supervision level. Proportional-integral derivative (PID) type controllers are used in the basic level to perform basic control functions while the decoupling between two control loops can be realized in the high level. A special subclass of fuzzy inference systems, called the Gaussian partition with evenly (GPE) spaced midpoints systems, is used to self-tune the main steam pressure PID controller's parameters online based on the error signal and its first difference, aimed at overcoming the uncertainties due to changing fuel calorific value, machine wear, contamination of the boiler heating surfaces and plant modeling errors. For the large variation of operating condition, a supervisory control level has been developed by autotuning technique. The developed CCS has been implemented in a power plant in China, and satisfactory industrial operation results demonstrate that the proposed control strategy has enhanced the adaptability and robustness of the process. Indeed, better control performance and economic benefit have been achieved.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TCST.2005.854319</doi><tpages>12</tpages></addata></record>
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subjects 20 FOSSIL-FUELED POWER PLANTS
Applied sciences
Automatic control
Boiler-turbine coordinated control strategy
BOILERS
Carbon capture and storage
COAL
Coal-fired power plants
Computer science
control theory
systems
CONTROL SYSTEMS
Control theory. Systems
decoupling control
Electric power generation
Electric power plants
Energy
Energy. Thermal use of fuels
Exact sciences and technology
FOSSIL-FUEL POWER PLANTS
industrial application
Installations for energy generation and conversion: thermal and electrical energy
Mathematical models
Modelling and identification
multivariable systems
PD control
Pi control
Power generation
power plant
Pressure control
Proportional control
Steam electric power generation
STEAM TURBINES
Strategy
Studies
Thermal power plants
Three-term control
Uncertainty
title A new coordinated control strategy for boiler-turbine system of coal-fired power plant
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