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Tomakomai mill thermal power station consists of seven boilers and 13 turbines and can provide you with all of mill electricity demand by self generation including hydraulic power generation.In a boiler plant, the thing which passed increased the above than operation for 25 years and I took into account the present driving results and did a review and did update to a reasonable fan more in turn since 1997. In addition, you should have promoted saving energy more and carried out a start stop in the weekend of a boiler turbine. I introduce the details to the following.

A nonlinear dynamic model for natural circulation drum-boilers is presented. The model describes the complicated dynamics of the drum, downcomer, and riser components. It is derived from first principles, and is characterized by a few physical parameters. A strong effort has been made to strike a balance between fidelity and simplicity. Results from validation of the model against unique plant data are presented. The model describes the behavior of the system over a wide operating range.

Based on analyzing the characteristics of Ultra-supercritical unit, this paper introduced a multiple model MCPC (Multivariable Constrained Predictive Control) structure with three inputs and three outputs for coordination control of Ultra-supercritical unit. In the structure, double-layer structure of optimization was used to obtain good steady and dynamic performance, and piecewise linear models at the different operating points of Ultra-supercritical unit were used to deal with nonlinearity. In the real-time simulation, nonlinear model of 1000MW Ultra-supercritical unit in [1] was considered. Finally, the result of real-time simulation was given in the paper.

Feedback stabilization of boiler-turbine system is discussed by using finite time control technique. First, boiler-turbine system is state feedback linearized. Then, by virtue of finite time control technique, series controllers and parallel controllers are designed respectively to stabilize boiler-turbine system. The closed-loop system exhibits faster convergence, better robustness and disturbance rejection properties. Simulations are employed to verify the proposed method.

This paper presents a new nonlinear coordinated control strategy for overcoming the influence of process nonlinearities and improving the load-following capability of coal-fired boiler-turbine units. A feedback linearization law is deduced via the dynamic extension algorithm of vector relative degree for a typical boiler-turbine unit model. By the law, exactitude feedback linearization in universal can be realized. And then a two-degree-of-freedom I-PD structure is presented to improve the robustness and exact tracking ability of the pseudo-linear object which is obtained by the feedback linearization law. The parameters of I and PD controllers are tuned by comparing with the corresponding coefficients of an anticipant close-loop transfer function matrix. Several simulations based on a real 500 MW boiler-turbine unit model are tested to prove the performance of the developed nonlinear coordinated control strategy.

Due to the characteristics of multi-variable, nonlinear, time varying, coupling and large time-delay of the boiler-turbine coordinated control system in power station, it's impossible to establish accurate mathematic model by traditional methods. RBF neural network can be used to identify nonlinear model effectively. A 160 MW nonlinear coordinated control model described by a group of differential equations is chosen in this paper. The drum pressure, power and water level of the coordinated control model are identified by RBF. Simulation results show that this strategy is effective. At the same time, the coordinated control strategy based on RBF is also discussed in this paper.

MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In the present work the control of boiler turbine process with three manipulated variables namely fuel flow valve position, steam control valve position and feed water flow valve position and three controlled variables namely drum pressure, output power and drum water level deviation [8] has been attempted using MPC technique. Boiler turbine process is very complex and nonlinear multivariable process. A linearized model obtained using Taylor series expansion around operating point has been used.

Linear control of a boiler-turbine unit is discussed in this paper. Based on the nonlinear model of the unit, this paper analyzes the nonlinearity of the unit, and selects the appropriate operating points so that the linear controller can achieve wide-range performance. Simulation and experimental results at the No. 4 Unit at the Dalate Power Plant show that the linear controller can achieve the desired performance under a specific range of load variations.

From the model of a 330 MW boiler-turbine system, a fuzzy multi-model control system (FMMC) based dynamic decouple PID and dynamic feedforward of boiler controller has been designed. The control system can overcome nonlinear, couple and large-lag etc. problems of boiler-turbine coordinated control system. Practical application proved the validity of the control method

This paper deals with the application of a Multivariable Nonlinear Controller (MNC) to a multivariable nonlinear boiler-turbine unit. The method can asymptotically estimate and compensate the nonlinearity, coupling and disturbances owing to its observation ability. A decentralized MNC system is obtained for a nonlinear boiler-turbine model, and then evaluated under a wide range of operating conditions and perturbations. Simulation results show that the MNC can achieve decoupling, asymptotic tracking property without steady-state errors, disturbance rejection and better robust performance for boiler-turbine plants, compared with GA/LQR and standard optimal controller LQR.

The main idea in life extending control (LEC), also known as damage mitigating control, is to redesign the controller in order to achieve a better tradeoff between structural durability and dynamic performance in a system. This task involves both damage dynamics modeling and LEC design. In this paper, we propose a new hierarchical LEC structure and apply it to a typical boiler system. There are two damage models in this structure: Model I is for online LEC and Model II is for online life prediction for critical components of the system. For Model I, we incorporate the improved rainflow cycle counting method and a continuous-time damage modeling approach. While for Model II, we choose a method based on the P-K theory which involves the mean stress effect. Finally, an optimal LEC scheme is proposed and simulation results show that the designed LEC substantially reduces the accumulated damage with a minimum loss of dynamic performance.

We present a simplified state-space model of a once-through supercritical boiler turbine power plant. This phenomenological model has been developed from a greatly simplified application of the first principles of physical laws. When we fit our model to a far more complex and physically accurate simulation model commissioned by EPRI for operator training, we find that the input-output responses are surprisingly close. Encouraged by this initial success, we describe some initial steps toward a design method for supercritical boiler control suggested by the geometric structure arising from the simplified model. Preliminary simulation results suggest that this approach may offer a closed loop response considerably improved relative to that achieved by the linear controllers presently in place in typical industrial settings.

The Hub project is located on the Arabian Sea coast of Pakistan in the province of Baluchistan and approximately 45 km from Karachi. The station has four 323 MW boiler turbine generator units of conventional design and burning heavy fuel oil. The design of the plant was conventional having a low level of technology risk. This project was arguably the largest privately financed power project in South East Asia. The fuel oil is supplied via an 80 km pipeline from the Pakistan State Oil Company terminal east of Karachi and the electricity generated is supplied into the 500 kV system owned and operated by the nationalised Water and Power Development Authority (WAPDA).

In this paper, a multivaribale robust controller for the boiler-turbine system is designed by using the LQG/LTR method. From the known nonlinear dynamic model, a linearized model is obtained with the saturations at both control inputs and their rates and the modeling error is analyzed at various operating points. The controller is designed using the LQG/LTR method to reject the input and output disturbances and to follow reference inputs under modeling errors. A dynamics augmentation method in the LQG/LTR method is suggested. The good performance of the designed controller is shown by simulations in various conditions.

The paper concentrates on the practical aspects of using pseudo random binary sequence perturbations to identify the dynamics of an operational 500MW boiler turbine unit. The usual method of testing, with automatic control loops open, is shown to be prone to difficulties, and the merits of testing closed loop systems are discussed. Correlation functions and frequency responses were computed from the test data and the information used to construct linear analogue models of the closed loop systems. Results are presented for a number of boiler transfer functions, chosen to illustrate the range of the work and some of the typical problems encountered.

Using mathematical models developed from real plant data, optimal control schemes for Boiler-Turbine plant are developed and their performance compared with existing boiler-follow control. Advantages and disadvantages of the schemes are discussed.

A procedure for the design of optimal nonlinear controllers for linear plants is presented. The procedure is based on the minimization of a performance index which is nonquadratic in the system states. The resulting closed loop system is asymptotically stable and its response is dependent on the magnitude of the system disturbance. An application to the control of a boiler-turbine system is considered.

This paper describes a microprocessor-based simulator of a Boiler-Turbine Plant, and control studies that have been carried out on the simulator. The simulator adequately represents the major plant dynamics and dynamic interactions and special attention has been paid to modelling the existing plant automatic control systems. Speeds of simulation of up to 20 x real time have been achieved, and operation of the system is simply obtained from a computer keyboard. The major simulator output is a graphic display of up to seven system variables against time.

Fast valving by momentary closing of turbine intercept valves will effectively improve transient stability. However, momentary closing of intercept valves may cause a disturbance in the boiler, turbine, and control systems. The effects on these systems should be considered in the application of fast valving Digital simulation using a model which represented a large fossil-fired unit in a multimachine system was performed, and the effects on the unit were analyzed and provisions for application of fast valving were considered. The results of studies indicate that no problems 'are expected in the application of fast valving on the large unit, and only minor modification is necessary to implement fast valving.

The paper describes the preparation for, and current practice of, daily intermittent, or ‘two-shift’, operation of large modern oil-fired 500 MW generating units by the South Western Region of the Central Electricity Generating Board at Fawley and Pembroke 2000 MW power stations.

A method is described for the determination of the amount of silica entrained in the steam of high-pressure boilers employed in large power stations, using silicon-31 as radioactive tracer. Good correlation was obtained with cases of known turbine blade deposition and the results have been used to decrease silica entertainment.

In this paper, a new hybrid jump PSO (HJPSO) is proposed for tuning the gains of PI controllers to the boiler turbine unit. HJPSO based Gaussian and Cauchy mutation is proposed to improve the standard PSO performance. The new strategy is based on observing the local and global best particles which are not improved in a predefined number of iterations and moving these particles to a new best position. Besides, forming a new particle that handles the minimum error of each controller to replace the global best particle if it has best fitness. The simulation results show that the proposed algorithm has its ability in optimizing the control parameters and effectively achieved better performance when compared with other PSO algorithms.

WHEN Oswego Steam Station of the Niagara Mohawk Power Corporation was being designed in the late 1930's, a unit system was decided upon, a unit consisting of a boiler, turbine, and generator. No steam, feed water, or electric interconnections at greater voltage were provided between units. The merits of the unit system in this case have been described elsewhere.1 The controls for such a station required an entirely new approach and presented an opportunity for major improvement.

In the analysis of power systems it is highly desirable to have models of the different power generators. In this paper we present, a model for a drum boiler whose purpose is to describe the gross behaviour of the boiler. The major control variables are fuel flow and control valve setting. The output variables are drum pressure and active output power. The model is verified by experiments on a 160 Mw boiler.