• 제목/요약/키워드: Steam temperature control, PI control

검색결과 9건 처리시간 0.028초

화력발전소의 과열기증기의 온도제어 (Temperature Control of Superheater Steam in Thermal Power Plant)

  • 신휘범;이순영
    • 전기학회논문지
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    • 제59권11호
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    • pp.2006-2011
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    • 2010
  • The superheater in the thermal power plant makes the wet steam into the dry steam with high temperature and high pressure by using the boiler heat. The dry steam pressure rotates the turbine-generator system. The efficiency and life time of the boiler heavily depends on the steam temperature regulation. The steam temperature can be deviated from the reference by the MW demand of the power plant. It is therefore required that the PI(proportional-integral) controller should be robust against the disturbance such as the MW demand. In this paper, the PI controller with the integral state predictor is proposed and applied to regulate the steam temperature of the superheater, and it is compared with the conventional PI controller operated in the thermal power plant in view of control performance.

화력발전소에서 과열저감기의 증기온도제어 (Steam Temperature Control of Attemperator in Thermal Power Plant)

  • 신휘범
    • 조명전기설비학회논문지
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    • 제25권7호
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    • pp.40-48
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    • 2011
  • An attemperator is a part of the 4-stage superheater in the boiler system of the thermal power plant. The attemperator receives the over-heated steam and makes the steam with proper temperature by adjusting the control valve of the cold steam. In this paper, the attemperator is modeled considering physical point of view and the linearized model is derived for the control purpose. To overcome the integral windup phenomenon due to the opening limitation of the control valve, an anti-windup PI controller is proposed to the attemperator and compared with the PI controller operated in the thermal power plant in view of control performance.

PI-신경망 제어기를 이용한 원자력 발전소용 증기 발생기 수위제어 (The level control of Steam Generator in Nuclear Power Plant by Neural Network-PI Controller)

  • 김동화
    • 조명전기설비학회논문지
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    • 제12권4호
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    • pp.6-13
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    • 1998
  • 본 연구에서는 증기유량, 중기온도 주 급수 온도 및 유량둥과 같은 외란에 의해 증기발생기의 웅축 및 팽창효 과가 발생하여 수위조절에 어려웅이 발생하는 문제를 신경망-PI제어기를 이용해 효과적으로 제어하는 연구를 하였다. 종래의 PI제어기는 저 출력에서 효과적으로 제어 할 수 없어 기동시는 숙련자의 노련한 기술이 필요한데 반해 본 연구에서 적용한 신경망 PI제어기는 Kp,Ti 파라매터를 외란에 영향을 줄 수 있는 파라메터를 고려하여 신경망을 이용해 튜닝함으로서 웅축 및 팽창효과를 줄이고 외란 및 설정치 변경에 대해 효과적으로 제어 될 수 있음을 실험과 시뮬레이션을 통해 확인 할 수 있었다.

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혼합 $H_{\infty}$ 최적화 기법을 이용한 견실 $H_{\infty}$ 증기발생기 수위제어기 설계 (Robust $H_{\infty}$ Controller Design for Steam Generator Water Level Control using Mixed $H_{\infty}$ Optimization Method)

  • 서성환;조희수;박홍배
    • 제어로봇시스템학회논문지
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    • 제5권3호
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    • pp.363-369
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    • 1999
  • In this paper, we design the robust $H_{\infty}$ controller for water level control of steam generator using a mixed $H_{\infty}$ optimization with model-matching method. Firstly we choose the desired model which has good disturbance rejection performance. Secondly we design a stabilizing controller to keep the model-matching error small and also provide sufficiently large stability margin against additive perturbations of the nominal plant. Simulation results show that proposed robust $H_{\infty}$ controller at specific power operation has satisfactory performances against the variations of load power, steam flow rate, primary circuit coolant temperature, and feedwater temperature. It can be also observed that the proposed robust $H_{\infty}$ controller exhibits better robust stability than conventional PI controller.

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신경망 2-자유도 PID제어기를 이용한 원자력 발전소용 증기 발생기 수위제어 (The level control of steam generator in nuclear power plant by neural network 2-DOF PID controller)

  • 김동화;이원규
    • 제어로봇시스템학회논문지
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    • 제4권3호
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    • pp.321-328
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    • 1998
  • When we control the level of the steam generator in the nuclear power plants, a swell and shrink arises from many disturbances such as feed water rate, feed water temperature, main steam flow rate, and coolant temperature. If we use the conventional type of PI controller in this system, we will not have stability during controlling at lower power, the removal function of disturbances, and a load follow-up control effectively. In this paper, we study the application of a 2-Degree of Freedom(2-DOF) PID controller to the level control of the steam. generator of nuclear power plants through the simulation and the experimental steam generator. We use the parameters $\alpha$, $\beta$, $\gamma$ of the 2-DOF PID controller for the removal of disturbances and the parameters Kp,Ti,Td of the conventional type of PID controller for controlling setpoint. The back-propagation learning algorithm of neural network is used for tuning the 2-DOF PID controller. We can find satisfactory results of the removal of the disturbances and the tracking function in the change of setpoint through the simulation and experimental steam generator.

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1kW 연료전지 시스템용 개질기 온도제어 (Temperature Control for the Steam Reforming Reactor in 1kW PEMFC system)

  • 신범수;김동찬;공민석;최동민;박연구
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회B
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    • pp.3136-3139
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    • 2008
  • The object of the paper is to design two PI controllers. One provides the stable target temperature to the steam reforming reactor in 1kW PEMFC system. The other controls burner to operate within a permissible range of temperature. Feedforward control is applied to obtain temperature stability against disturbances such as changes of operating condition resulted from load change. Step response tests show that these controller work well with an error tolerance of $5^{\circ}C$.

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Adaptive Intelligent Control of Inverted Pendulum Using Immune Fuzzy Fusion

  • Kim, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.2372-2377
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    • 2003
  • Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,{\dot{x}},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

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Adaptive Intelligent Control of Nonlinear dynamic system Using Immune Fuzzy Fusion

  • Kim, Dong-Hwa;Park, Jin-Ill
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제3권2호
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    • pp.146-156
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    • 2003
  • Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,\dot{x},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

Multiobjective PI Controller Tuning of Multivariable Boiler Control System Using Immune Algorithm

  • Kim, Dong-Hwa;Park, Jin-Ill
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제3권1호
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    • pp.78-86
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    • 2003
  • Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.