• Journal of Electrical Engineering and Technology
• /
• v.6 no.3
• /
• pp.423-430
• /
• 2011

Multi-input multi-output (MIMO) dynamic matrix control (DMC) technique is applied to control steam temperatures in a large-scale ultrasupercritical once-through boiler-turbine system. Specifically, four output variables (i.e., outlet temperatures of platen superheater, finish superheater, primary reheater, and finish reheater) are controlled using four input variables (i.e., two spray valves, bypass valve, and damper). The step-response matrix for the MIMO DMC is constructed using the four input and the four output variables. Online optimization is performed for the MIMO DMC using the model predictive control technique. The MIMO DMC controller is implemented in a full-scope power plant simulator with satisfactory performance.

• Proceedings of the SAREK Conference
• /
• 2009.06a
• /
• pp.167-171
• /
• 2009

We conducted performance test of a 350 kW class wood pellet boiler installed at a dormitory whose total area is $1,354\;m^2$. The maximum heating capacity of the boiler is 350 kW(300,000 kcal/kg). The wood pellet boiler consists of 3 parts; boiler, hot water storage tank and wood pellet storage tank. In testing the boiler, we shut off hot water utility supply and open up floor heating water system in order to measure exact value of the heating output of the wood pellet boiler. To determine the efficiency and heating output of the wood pellet boiler, we measured mass flow rate of wood pellet, the lower heating value(LHV) of the wood pellet, mass flow rate and temperature of water for floor heating and so on. We measured the mass flow rate of fuel, wood pellet with respect to rotational speed of auger, wood pellet feeding screw. We also measured the flue gas concentration of the wood pellet boiler by using a gas analyser. The result shows that the efficiency of the wood pellet boiler is 80.6% based on lower heating value at 124 kW of heating output. At this condition, O2 concentration of the flue gas is 6.0%, CO and NOx concentrations are 85 and 102 ppm.

• 한국신재생에너지학회:학술대회논문집
• /
• 2010.11a
• /
• pp.103.1-103.1
• /
• 2010

Recently domestic wood pellet boilers are installed in rural and forestry houses. The fuel price per lower heating value of wood pellet is about 20 % lower than that of heating oil on July 2010. In spite of lower price of wood pellet, a few user of wood pellet boiler complain expensive fuel cost. One of this reason is inaccurate or improper air-fuel ratio setting of wood pellet boiler. O2 concentration of flue gas of domestic wood pellet boiler is about 9.7 % and there are few domestic wood pellet boiler which can control air-fuel ratio automatically. We tested a domestic wood pellet boiler in changing boiler thermal output and air-fuel ratio. The nominal boiler thermal output is 25 kW (21 500 kcal/h). We measured thermal efficiency and flue gas concentrations such as CO and NOx at each boiler thermal load with various air-fuel ratio. The results show that if air flow rate is the same as full load and part load, thermal efficiency of part load of 40 % drops about 7.7 %p compared to boiler full load case.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.687-692
• /
• 1991

To reduce the complexity in constructing a fuzzy logic controller of multivariable systems, three major methods are presented. One is the method of constructing single-input-single-output fuzzy logic controllers after decoupling the target system. Another is the method of using fuzzy relation matrices which indicate the relation between each input and output. The other is the method of using the hierarchically classified inputs which dominantly influence one output than other inputs. Using the last two methods, simulation results of fuzzy logic controller implemented on 160MW boiler-turbine plant model are also shown.

• Journal of Applied Reliability
• /
• v.14 no.1
• /
• pp.37-43
• /
• 2014

This paper deals with a design of observer based fault detection filter for a boiler-turbine control system. The goal is to present a method for rapid sensor fault detection in order to enhance the reliability of boiler-turbine operation in the thermal power plant. Our fault detection filter can be designed via solutions of linear matrix inequalities. In order to demonstrate the efficacy of our design method, numerical simulations are provided.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.160-163
• /
• 1996

This paper deals with MCMBPC(Multivariable Constrained Model Based Predictive Controller) for nonlinear boiler system with noise and disturbance. MCMBPC is designed by linear state space model obtained from some operating point of nonlinear boiler system and Kalman filter is used to estimate the state with noise and disturbance. The solution of optimization of the cost function constrained on input and/or output variables is achieved using quadratic programming, viz. singular value decomposition (SVD). The controller designed is shown to have excellent tracking performance via simulation applied to nonlinear dynamic drum boiler turbine model for 16OMW unit.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.323-325
• /
• 2009

In this paper, we present simulation results of Dynamic Matrix Control(DMC) to a boiler steam temperature. In order to control of steam temperature, we choose the input-output variables and generate the step response model by each input variable's step test. After that, the control structure executes on-line control with optimization using step response model. Proposed controller is applied to the APESS(Doosan company's boiler model simulator) and it is observed that the simulation results show satisfactory performance of proposed control.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.62 no.1
• /
• pp.36-44
• /
• 2013

This paper is written for the development and application of boiler fuel control algorithm and distributed control system of coal-fired power plant by the steps of design, coding, simulation test, site installation and site commissioning test. Fuel control algorithm has the upper algorithm and it is boiler master control algorithm that controls the fuel, feed water, air by generation output demand. Generation output demand by power load influences fuel control. Because fuel can not be supplied fast to the furnace of boiler, fuel control algorithm was designed adequately to control the steam temperature and to prevent the explosion of boiler. This control algorithms were coded to the control programs of distributed control systems which were developed domestically for the first time. Simulator for coal-fired power plant was used in the test step. After all of distributed control systems were connected to the simulator, the tests of the actual power plant were performed successfully. The reliability was obtained enough to be installed at the actual power plant and all of distributed control systems had been installed at power plant and all signals were connected mutually. Tests for reliability and safety of plant operation were completed successfully and power plant is being operated commercially. It is expected that the project result will contribute to the safe operation of domestic new and retrofit power plants, the self-reliance of coal-fired power plant control technique and overseas business for power plant.

• 한국신재생에너지학회:학술대회논문집
• /
• 2008.05a
• /
• pp.194-197
• /
• 2008

We measured the efficiency and flue gas concentration of a 90kW woodchip boiler which is for heating water of lodging. At nominal operating condition, the fuel, woodchip is fed into the boiler at a rate of 22.6 kg/h. In order to determine the efficiency of the boiler, we measured the water flow rate, woodchip flow rate, heating value and water content of woodchip, temperature of inlet and outlet of heating water. The results of test show that the power output of the woodchip boiler is 90.0 kW(77,400 kcal/h) and the thermal efficiency of the boiler is 88.5%. By using a gas analyser, flue gas concentrations are measured. The results show that O2 in the flue gas is 10.2%, CO concentration is 393 ppm and NOx concentration is 74 ppm.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.798-800
• /
• 1995

The neural network predictive controller(NNPC) is proposed for the attempt to mimic the function of brain that forecasts the future. It consists of two loops, one is for the prediction of output(Neural Network Predictor) and the other one is for control the plant(Neural Network Controller). The output of NNC makes the control input of plant, which is followed by the variation of both plant error and prediction error. The NNP forecasts the future output based upon the current control input and the estimated control output. The method is applied to the control of temperature in boiler systems. The proposed NNPC is compared with the other conventional control methods such as PID controller, neural network controller with specialized learning architecture, and one-step-ahead controller. The computer simulation and experimental results show that the proposed method has better performances than the other methods.