Drum Water Level Research Articles

Active Disturbance Rejection Control Design with Sensitivity Constraint for Drum Water Level

The drum water level plays a crucial role in the safety and economy of heat recovery boilers. However, the control of the drum water level faces many challenges, such as external disturbances and system uncertainties. To enhance the control performance of the drum water level, a modified active disturbance rejection control (MADRC) optimized with sensitivity constraint is proposed in this paper. Firstly, the control structure of the three-element control system for the drum water level is introduced and analyzed. Based on the regular active disturbance rejection control (ADRC) structure, the structure of the MADRC is introduced and the convergence of the proposed MADRC is proven. Then a modified whale optimization algorithm (MWOA) with sensitivity constraint is applied to optimize the parameters of the MADRC. With different sensitivity constraints, the parameters of the MADRC and comparative controllers are obtained, and their control performance for tracking and disturbance rejection abilities is compared. Moreover, the ability to handle system uncertainties is analyzed. Simulation results and performance indexes show that the proposed MADRC can obtain the best tracking and disturbance rejection abilities with satisfactory robustness. The satisfactory control performance shows that the proposed MADRC has wide application potential for heat recovery boilers and other industrial processes.

Drum boiler system water level control: A study of existing hybrid optimization algorithms

In this research, we use a variety of optimization techniques to perfect the settings of a PID controller that manages the water level in a boiler's drum. In this study, Particle Swarm Optimization (P_S OPTIMIZATION) is used alongside other optimization techniques and compared to each other. Optimization that combines bacterial foraging with Particle swarms (BFP_S) and Hybridising the Gravitational Search Algorithm along with Particle swarm (GSAP_S) seeks to improve search results. The forementioned methods were tested, and their results were compared, utilising metrics such as IS ERROR, IA ERROR, ITA ERROR, and time domain specifications.

Novel modelling for a steam boiler under fast load dynamics with implications to control

This paper describes a new nonlinear dynamic model for a natural circulation boiler. The model is based on physical principles, i.e. mass, energy and momentum balances. A systematic approach is followed leading to new insights into the physics of drum water level and downcomer mass flow. The model captures fast dynamic responses that are necessary to describe the operation of a boiler under highly variable load conditions. New features of the model include (i) a multi-compartment model for the risers, (ii) a new model for drum water level, and (iii) a new dynamic model for the flow of water in the downcomers. Implications of the model for control system design are explored in detail. Finally, the suggested improvements are validated in a sugar mill boiler (50 [MW] Babcock & Wilcox water-tube boiler).

Dynamic modeling of Boiler drum using nonlinear system identification approach

Thermal power generation plays a major role in meeting present-day power demands. Efficient and economic controls of crucial elements like steam boiler section need superior control mechanism to ensure better efficiency. Identification of model, dynamics is a formidable task due to the strong coupling of process variables, nonlinearities in the dynamics and constraints on the control inputs. This paper presents the application of nonlinear modeling techniques to estimate boiler drum dynamics in terms of nonlinear model framework which is one of the important requirements for the design of drum water level controls schemes. The historical plant data for estimation is collected from boiler of 210 MW, Stage-II, Boiler-4 of Dr. Narla Tata Rao Thermal power Corporation (NTTPC) Ibrahimpatnam, Vijayawada. Different operating conditions are selected to estimate the nonlinear dynamics of the boiler to check with the existing Hammerstein, Wiener, model frame works. Later the nonlinear framework is modified to estimate other nonlinearities present in the system. The estimated model responses are presented to check the boiler dynamics.

Model-based dynamic sliding mode control and adaptive Kalman filter design for boiler-turbine energy conversion system

The model-based control of a boiler-turbine system (BTS) is a formidable task due to coupling in state variables, nonlinearities and constraints on the control inputs. In this paper, a model-based, multi-variable dynamic sliding mode control (DSMC) is designed for the nonlinear BTS model to maintain the drum pressure, electric power and water level at the desired levels. In DSMC, an implicit sliding manifold is designed for the water level due to its complexity and explicit dependence on the control inputs. For this purpose, an auxiliary function is computed, and the sliding mode is enforced in such a way that the system fluid density tracks the auxiliary function, and subsequently the water level tracks the desired trajectory. Owing to its complexity, the time derivatives of the auxiliary function are computed using the uniform robust exact differentiator (URED). An adaptive Kalman filter (AKF) is designed for the estimation of the unmeasurable state i.e., system fluid density. The design of AKF is based on the quasi-linear model of the BTS. Furthermore, a detailed stability analysis is carried out to ensure the boundedness of the closed-loop system. The simulation results depict that the designed control scheme exhibits the desired tracking performance in the presence of external disturbances, nonlinearities, constraints on the inputs, and measurement and process noises.

Data-driven adaptive-critic optimal output regulation towards water level control of boiler-turbine systems

This paper considers a new adaptive-critic optimal output regulation scheme for continuous-time general linear systems with unknown dynamics and unmeasurable disturbance. The objective of researching the optimal output regulation problem is pursuing the stability of the closed-loop system while enabling the output to optimally track the reference signal with disturbance rejection. The problem is solved by employing an approximate optimal regulator that consist of optimal feedback control obtained by a data-driven learning algorithm and optimal feedforward control achieved by solving regulator equation. The missing system matrices of the plant are exactly figured out by employing state/input data. Moreover, by employing the minimal polynomial of the exosystem matrix, the parameter of interference in the output equation is available. Then, a predefined cost function is presented based on the regulator equation that aims to design the optimal control law. The stability analysis demonstrate that the presented control scheme can stabilize the closed-loop system, meanwhile the output asymptotically tracks the reference signal. Finally, the effectiveness of the developed optimal control scheme is validated through an application towards the drum water level control of boiler-turbine systems.

Dynamic modeling of a water tube boiler

AbstractThe present work aims to develop an integrated heat transfer and hydrodynamic model for the study of boiler dynamics in fluctuating load conditions. A transient heat transfer model has been developed to estimate water side heat transfer and it is directly integrated with the hydrodynamic model. Two independent natural circulation circuits for furnace water wall and convection tube bank have been considered due to differences in heat transfer, dryness fraction, and void fraction. The transient heat transfer model calculates the heat transfer and water wall temperature of the various sections to calculate total gas side heat transfer, gas temperature profile, and waterside heat transfer in the furnace water wall and convection tube bank. Mass momentum and energy conservation equations are generated for both natural circulation circuits using the estimated value of waterside heat transfer of the transient heat transfer model. These equations are integrated with mass and energy conservation equations for the drum below water level and drum above water level to generate a system of equations to estimate drum pressure and water level fluctuation. This model has been extended for boiler feedback control systems, including the load management and the water level control system.

Self-Tuning PID-Genetic Algorithm Controller for Steam Drum Boiler Water Level Control System

A control system with uncertainty or unpredictable disturbance needs more effort to be controlled. A conventional PID Controller is the most popular method used in industries. It was tuned and adjusted by the designer, and it has fixed parameters during operation. However, the disturbance effect causes the desired system performance unreachable. By using a self-tuning controller, the problem should be tackled. In this paper, the PID-Genetic Algorithm (PID-GA) controller was proposed and tested with the steam drum water level control system of a steam power plant. Variation in power load causes noisy water level characteristics and should be maintained at + 0.4 meters from the setpoint to prevent the power plant trip. From the simulation, PID-GA can reduce disturbance of the minimum, nominal, and maximum load with perturbation peaks 0.18 m, 0.22 m, and 0.26 m respectively.Keywords: genetic algorithm, NWL, PID-GA, steam drum, steam power plant.

Tuepras upgrades Izmit refinery to expand diesel production

In this paper, various optimization techniques for the parameter tuning of a P.D controller to control the water level in a boiler drum have been applied. The optimization techniques utilized and compared in this paper are 1) Particle Swarm Optimization (PSO) 2) Bacterial Foraging – Particle Swarm Optimization hybrid (BFPSO) 3) Gravitational Search Algorithm – Particle Swarm Optimization hybrid (GSAPSO). A comparative study of the above-mentioned optimization techniques was done based on the time domain characteristics and performance indices namely, Integral Square Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Error (ITAE).

WITHDRAWN: Comparison and analysis of hybrid optimization algorithms for water level control of drum boiler system

In this paper, various optimization techniques for the parameter tuning of a P.D controller to control the water level in a boiler drum have been applied. The optimization techniques utilized and compared in this paper are 1) Particle Swarm Optimization (PSO) 2) Bacterial Foraging – Particle Swarm Optimization hybrid (BFPSO) 3) Gravitational Search Algorithm – Particle Swarm Optimization hybrid (GSAPSO). A comparative study of the above-mentioned optimization techniques was done based on the time domain characteristics and performance indices namely, Integral Square Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Error (ITAE).

Anti-noise model-free adaptive control and its application in the circulating fluidized bed boiler

Model-free adaptive control has been developed greatly since it was proposed. Up to now, model-free adaptive control theory has become mature and tends to be an effective solution for complex unmodeled industrial systems. In practical industrial processes, most control systems are inevitably accompanied by noise that will result in indelible error and may further cause inaccurate feedback to the output. In order to solve this kind of problem with model-free technique, this article incorporates an improved tracking differentiator into model-free adaptive control. After that, the anti-noise model-free adaptive control method with complete convergence analysis is proposed. Meanwhile, numerical simulation proves that the improved control method can quickly track a given signal with good resistance to noise interference. Finally, the effectiveness and practicability of the proposed algorithm are verified by experiments through the control of drum water level of circulating fluidized.

A GRU Network-Based Approach for Steam Drum Water Level Predictions

A GRU Network-Based Approach for Steam Drum Water Level Predictions

Fuzzy control and simulation of boiler drum water level

Boiler drum water level control system is hard to develop practical mathematical model and has nonlinear, stable and delay characteristics. The traditional boiler drum water level control often uses three impulse PID control method. The existing problem of ordinary PID control strategy is: once good parameter setting, it is hard to adapt to the change of the operation of the system dynamic greatly. In order to solve the problems of the above, the research object of the subject is a certain 120 t/h boiler steam capacity, the boiler drum water level control system is designed, and the control strategies are studied. In order to obtain better contrast, the ordinary PID controller and Fuzzy controller are designed, and the control strategies of the simulation are analyzed.

Analysis and treatment of abnormal shutdown of 150MW unit due to low feed water flow

The water level of NO.2 high pressure heater rised when the 150MW turbogenerator set of a power plant operated normally, it was unassembled and checked. After the high pressure heater was put into operation, the water level of the boiler drum droped. After the standby electric pump was started and the electric load was reduced, the water level of the boiler drum still droped, resulting in the boiler feed water flow reduced to the protection action and the unit shutdown. Through inspection, it was found that the connecting rod pin of the manual valve at the outlet of the high-pressure heater was broken, which maked the manual valve at the outlet not fully open and lead to low water flow rate at the water side of the high-pressure heater.After the corresponding improvement and optimization measures were taken, the unit can be restarted and run normally .

Mathematical Modeling of Transient Processes of the Automatic Control System of Water Level in the Steam Generator

The methodology of creation of automatic control system (ACS) of water level in the steam generator is developed. The mathematical model of checking its working capacity is developed, which allows establishing the maximum deviations of water level without carrying out full-scale tests, without adjusting the settings of tripping actuation according to the water level in the drum. The foreign methods of PID-regulator adjustment in the cascade system of automatic water level control in the boiler drum are considered, on the basis of which an invariant cascade system of automatic control is proposed. The invariant Cascade-System of Automatic Control (CSAC) of water level in a boiler drum is offered. Simulation results of the invariant cascade-system of automatic control in comparison with CSAC, configured with best foreign method, showed a significant improvement in the quality of regulation in all the major disturbing influences. The results can be used in the development of adaptive control systems and other thermal power devices.

Features of Automatic Control of Technological Parameters of Water Level in the Drum Steam Boilers

The three-pulse system of automatic control of the water level in the boiler drum received maximum distribution in the energy sector, as well as its modifications, which have the following disadvantages : the presence of static control errors at the end of the transition process in the development of internal disturbances and disturbances of superheated steam flow; large level deviations with sharp and significant changes in the load, which often leads to unloading or shutdown of the boiler or power unit. To eliminate these drawbacks, invariant systems for automatic regulation of the power supply of the drum boiler were previously developed. In work the system of automatic control of technological parameters of water level in a drum of steam boilers is considered. The description of control systems and a detailed description of the electrical power systems of the control system are given. Various methods of tuning the PI controller of a typical three-pulse automatic power control system are considered. The application of the method of structural-parametric optimization and the theory of invariance makes it possible by changing the structure of the system and optimizing the dynamic adjustment of the automatic power control system to significantly improve the quality of maintaining the water level in the boiler drum. Invariant automatic control systems eliminate static control errors under all influences and can significantly improve the quality of maintaining the level under variable conditions. The methods are proposed to significantly improve the quality of water level control in the boiler drum, eliminating the shortcomings of the typical automatic control system. The results of the work can be used in the design of power control systems of steam drum boilers. The results obtained can be used in the development of adaptive control systems for other thermal power facilities.

Drum Water Level Control Based on Improved ADRC

Drum water level systems show strong disturbance, big inertia, large time delay, and non-linearity characteristics. In order to improve the antidisturbance performance and robustness of the traditional active disturbance rejection controller (ADRC), an improved linear active disturbance rejection controller (ILADRC) for drum water level is designed. On the basis of the linear active disturbance rejection controller (LADRC) structure, an identical linear extended state observer (ESO) is added with the same parameters as that of the original one. The estimation error value of the total disturbance is introduced, and the estimation error of the total disturbance is compensated, which can improve the control system’s ability to suppress unknown disturbances, so as to improve the antidisturbance performance and robustness. The antijamming performance and robustness of LADRC and ILADRC for drum water level are simulated and analyzed under the influence of external disturbance and model parameter variation. Results show that the proposed control system ILADRC has shorter settling time, smaller overshot, and strong anti-interference ability and robustness. It has better performance than the LADRC and has certain application value in engineering.

Study on Startup Control Characteristics for CSR1000

The analysis of the startup system and startup characteristics are one important part of SCWRs design. In order to realize the analysis of the whole startup system, this paper proposes the new wall heat transfer model, based on the supercritical transient analysis code named SCTRAN. Then, the paper presents a control strategy for the startup process, including the control of coolant flow rate, core inlet temperature, system pressure, core thermal power, and steam drum water level. Different control schemes are set up according to different control objectives of the startup phases. Based on the CSR1000, an analytical model including the circulation loop and the once-through direct cycle loop is established, and four startup processes with control systems are put forward. The calculation results show that the thermal parameters of the circulation loop and the once-through direct cycle loop meet the expectation, and the maximum cladding surface temperature does not exceed the limit temperature 650℃. The feasibility of the startup scheme and the security of the startup process are verified.

Control and thermal analysis for SCWR startup

Startup system, the design of startup sequences analysis is an important part of SCWR design. A thermal hydraulic system analysis code for supercritical water reactor named SCTRAN is used to model the entire startup system based on the circulation loop for startup and once-through direct cycle. The problem of the heat transfer coefficient (HTC) does not accurately capture deterioration phenomenon, the HTC is calculated as a discontinuity in the mode transfer region, its low prediction accuracy above the quasi-critical region have been solved by the new wall heat transfer model. Especially, the look-up table would not be used to obtain the HTC and achieves high prediction accuracy across the critical region, unless the pressure is higher than 19 MPa. After that, to get a smooth recirculation variable pressure startup process, the system model integrates the control system which can controls the temperature, the steam drum water level, the thermal power, and the coolant flow rate. Based on the CSR1000 core and entire once-through direct cycle and circulation loop for startup, four stages under control systems, from low pressure to full power condition in recirculation startup process, were analyzed with code SCTRAN and wall heat transfer model was modified. The calculation results show that the recirculation system can startup from subcritical state to full power state without issue of CHF. The control system can control the parameters quite well and maximum cladding temperature (MCST) can be limited under 650 °C in the startup process. The modified SCTRAN code in this paper can further expand the computational range and computational accuracy. The full-scale control system can meet the needs of parameters expected response.

A nonlinear state‐feedback state‐feedforward tracking control strategy for a boiler‐turbine unit

AbstractA boiler‐turbine unit is a primary module for coal‐fired power plants, and an effective automatic control system is needed for the boiler‐turbine unit to track the load changes with the drum water level kept within an acceptable range. The aim of this paper is to develop a nonlinear tracking controller for the Bell‐Åström boiler‐turbine unit. A Takagi‐Sugeno fuzzy control system is introduced for the nonlinear modeling of the Bell‐Åström boiler‐turbine unit. Based on the Takagi‐Sugeno fuzzy models, a nonlinear tracking controller is developed, and the proposed control law is comprised of a state‐feedforward term and a state‐feedback term. The stability of the closed‐loop control system is analyzed on the basis of Lyapunov stability theory via the linear matrix inequality approach and Schur complement. Moreover, model uncertainties are also considered, and it is proved that with the proposed control law the tracking error converges to zero. To assess the performance of the proposed nonlinear state‐feedback state‐feedforward control strategy, a nonlinear model predictive control strategy and a linear strategy are presented as comparisons. The effectiveness and the advantages of the proposed nonlinear state‐feedback state‐feedforward control strategy are demonstrated by simulations.