Boiler-turbine Unit Research Articles

Multiobjective Operation of Ultra-Supercritical Boiler-Turbine Unit

Abstract In order to optimize the economic objectives while regulating the ultra-supercritical boiler-turbine unit, an improved utopia tracking based multiobjective fuzzy model predictive control is proposed in this paper. This method uses a hierarchical structure, in which the quasi-infinite horizon fuzzy model predictive control is designed for the steady-state compromise point in the upper layer and the utopia tracking based multiobjective control is devised in the lower layer. To ensure the closed-loop stability, a constraint with respect to the optimal value function about the compromise point is enforced. The simulation results on a 1000MW USC boiler-turbine unit model verify the merits of the proposed strategy in achieving less fuel consumption and less throttling loss during the load regulation.

Control of Nonlinear Constrained Ultra-Supercritical Boiler–Turbine Units Using Offset-Free Output-Feedback Stable MPC

Abstract It is extremely challenging to control ultra-supercritical boiler–turbine unit on account of its nonlinearity, coupling among multi-variables, hard input constraints, and unknown disturbances. An offset-free output-feedback stable model predictive control (MPC) (OFOF-SMPC) for nonlinear constrained ultra-supercritical boiler-turbine units is investigated. It is shown that the OFOF-SMPC is composed of a disturbance and state observer, a steady-state target calculator as well as a stable MPC, which can remove unknown disturbances from output channels and ensure the stability of the closed-loop system with input constraints. Simulation results demonstrate the effectiveness of the proposed algorithm.

A Novel Data Integrity Attack Detection Algorithm Based on Improved Grey Relational Analysis

False data injection (FDI) attack is the most common data integrity attack, and it is also one of the most serious threats in industrial control systems (ICSs). Although many detection approaches are developed with burgeoning research interests, the technical capability of existing detection methods is still insufficient because the stealth FDI attacks have been proven to bypass bad data detector. In this paper, a novel data analytical algorithm is proposed to identify the stealth FDI attacks in ICSs according to the correlation analysis. First, we evaluate the correlation between measurements and control variables based on an improved grey relational analysis. Then, SVM is used to classify the FDI attack according to the values of correlation. Through a reliable semi-physical simulation testbed whose virtual plant corresponds to a 330 MW boiler-turbine unit, two FDI attacks that can bypass the detection system are studied. A dataset, which contains the normal data and attack data, is created from the testbed to verify the effectiveness of the proposed algorithm. In addition, the performance of the proposed algorithm is also studied based on the new gas pipeline dataset that is collected by the distributed analytics and security institute in Mississippi State University. Such a novel algorithm, which has better accuracy and reliability, is compared with the state of the art based on the data analysis.

Design & application of adaptive variable structure &[formula omitted] robust optimal schemes in nonlinear control of boiler-turbine unit in the presence of various uncertainties

In this article, to improve the precision, performance and robustness of an industrial boiler-turbine, two robust controllers are designed. First, a robust adaptive variable structure control scheme (RAVSC) is proposed to control a nonlinear multi-inputs multi-outputs (MIMO) model of an industrial boiler-turbine unit, in the presence of significant uncertainties and external disturbances. To guarantee the reliable performance of the RAVSC, appropriate adaption and control laws are introduced to compensate the uncertainties and modeling imprecisions and guarantee the convergence to the sliding surface. Then, the robustness and stability of the proposed RAVSC is proved via Lyapunov stability theory. Moreover, a robust H∞ controller is designed based on μ−DKiteration , with assumption of presence rational deviation in parameters and suitable weights to attenuate the control signals. To investigate the performance of proposed control schemes, simulation studies are carried out on nonlinear dynamic model in the presence of various uncertainties. Then, the performance of designed robust controllers exposed to discussion which reveals the satisfactory performance of the both proposed controllers. However, it is observed that RAVSC has some minor advantages over the robust H∞ controller.

A Stable Multi-Objective Economic MPC Scheme for Boiler-Turbine Units

This paper proposes a compact boiler-turbine control scheme for the fossil-fuel power plants. Generally, control strategies used in boiler-turbine units are implemented as the hierarchical structures consisting of an upper economic optimization layer and a separate lower feedback control layer. The deficiency of such hierarchy is that the tracking of the steady-state set-points, that are computed by the upper layer, is accomplished by the lower layer in an economically non-optimal way. To improve the economic performance of boiler-turbine units, the proposed control scheme integrates plant economic optimization into the dynamic feedback controller output computation process. The stability (and also feasibility) of the proposed control scheme is proven. The effectiveness of the latter is also demonstrated through the 160 MW oil-fired boiler-turbine unit simulation.

Optimal partitioning of a boiler-turbine unit for Fuzzy model predictive control

In order to effectively control the multi-input multi-output (MIMO) characteristics of a boiler-turbine unit Fuzzy model predictive control (FMPC) has been previously applied successfully. An important step in the FMPC design is the partitioning (also called the design of the antecedent rules). In this work it is shown that by exploiting the plant characteristics and by using suitable metrics of the nonlinearity a representative one-dimensional partition space can be defined. Furthermore, it is demonstrated that a simple partition into two linear models suffices to obtain a stable and performing control system. In order to achieve this simple FMPC a nonlinear stationary feed-forward decoupling is implemented. Simulation results demonstrate stability and performance of the resulting control system even for large reference steps. The methodology developed in this work is quite general and can be easily applied to the FMPC design for other nonlinear MIMO plants.

OUTPUT FEEDBACK CONTROL WITH CONSTRAINTS FOR NONLINEAR SYSTEMS VIA PIECEWISE QUADRATIC OPTIMIZATION

Very few output feedback control methods can be applied for a large class of nonlinear objects. If the control problem has supplementary constraints to satisfy, the number of suitable methods will be fewer. The paper proposes a nonlinear control method, which can be applied to output tracking control a wide range of various perturbed nonlinear objects. This output feedback controller is established based on piecewise quadratic optimizing subjected to input constraints for state feedback control and then combined with an appropriate EKF or UKF for system state observation. The simulation results obtained by applying this proposed controller to output tracking control inverted pendulum and boiler-turbine unit had confirmed its promising applicability in practice.

${H}_{\infty }$-LQR-Based Coordinated Control for Large Coal-Fired Boiler–Turbine Generation Units

The coordinated control system of a boiler–turbine unit plays an important role in maintaining the balance of energy supply and demand, optimizing operational efficiency, and reducing pollutant emissions of the coal-fired power generation unit. The existing challenges (the fast response to wide-scaled load changes, the matching requirements between a boiler and a turbine, and cooperative operation of a large number of distributed devices) make the design of the coordinated controller for the boiler–turbine unit be a tough task. In this paper, based on a typical coal-fired power unit model, using the linear-quadratic regulator (LQR), a coordinated control scheme with $H_{\infty }$ performance is proposed: the $H_{\infty }$ method is used to ensure control performance on the basis of reasonable scheduling of distributed equipment; the LQR is applied to limit the control actions to meet the actuator saturation constraints. Case studies for a practical 500 MW coal-fired boiler–turbine unit model indicate that the designed control system has satisfactory performance in a wide operation range and has a very good boiler–turbine coordination capacity.

Fault detection and isolation system for boiler-turbine unit of a thermal power plant

In this study, a sensor fault detection and isolation (FDI) system is presented for a boiler-turbine unit of a thermal power plant in Mexico. The FDI system is based on a Luenberger-like observer for residual generation. An adaptive threshold for residual evaluation is considered to avoid false alarms. The observer is based on a quasi-linear parameter variant (quasi-LPV) model of the boiler-turbine unit parameterized with real data of the plant in a wide range of operations, namely, at low, medium, and high loads. The quasi-LPV model adequately represents the dynamics of more critical variables including first stage turbine pressure, superheated steam pressure, drum pressure, and electric power. The performance of the FDI system is evaluated in a practical scenario by using real data from the thermoelectric plant. The main contribution of this study involves proposing a reliable fault diagnosis system to detect sensor faults in a wide operational range of the process based on the quasi-LPV framework.

Extended state observer based fuzzy model predictive control for ultra-supercritical boiler-turbine unit

The regulation of ultra-supercritical (USC) boiler-turbine unit in large-scale power plants is vulnerable to various unknown disturbances, meanwhile, the internal nonlinearity makes it a challenging task for wide range load tracking. To overcome these two issues simultaneously, an extended state observer based fuzzy model predictive control is proposed for the USC boiler-turbine unit. Firstly, the fuzzy model of a 1000-MW coal-fired USC boiler-turbine unit is established through the nonlinearity analysis. Then a fuzzy stable model predictive controller is devised on the fuzzy model using output cost function for the purpose of wide range load tracking. An improved linear extended state observer, which can estimate plant behavior variations and unknown disturbances regardless of the direct feedthrough characteristic of the system, is synthesized with the predictive controller to enhance its disturbance rejection property. Closed-loop stability of the overall control system is guaranteed. Simulation results on a 1000-MW USC boiler-turbine unit model demonstrate the effectiveness of the proposed approach.

Nonlinear predictive control of a boiler-turbine unit: A state-space approach with successive on-line model linearisation and quadratic optimisation

This paper details development of a Model Predictive Control (MPC) algorithm for a boiler-turbine unit, which is a nonlinear multiple-input multiple-output process. The control objective is to follow set-point changes imposed on two state (output) variables and to satisfy constraints imposed on three inputs and one output. In order to obtain a computationally efficient control scheme, the state-space model is successively linearised on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimisation problem. For state estimation the extended Kalman filter is used. It is demonstrated that the MPC strategy based on constant linear models does not work satisfactorily for the boiler-turbine unit whereas the discussed algorithm with on-line successive model linearisation gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimisation repeated at each sampling instant.

A dynamic mathematical model of an ultra-supercritical coal fired once-through boiler-turbine unit

It is challenging and interesting to establish a precise dynamic model of an OTB (once-through boiler) power plant unit in order to meet large scale load demands from the power grid. This study proposes to establish such a dynamic mathematical model of an ultra-supercritical OTB unit under dry operating conditions. More precisely, the dynamic model structure was derived from mass and energy conservation laws as well as thermodynamic principles under some reasonable simplifications and assumptions. Then an IGA (immune genetic algorithm) was improved to identify the parameters, combined with running data. After this, to further enhance model performance, the dynamic mathematical model was extended to be the one with different sets of parameters and functions under different monotonous load ranges. Additionally, open- and closed-loop experiments were conducted in order to further validate the developed model. The experimental results show that the model outputs can approach the actual running data over a wide operating range with appropriate accuracy. More importantly, the dynamic model captures the essential dynamic characteristics of the unit. Therefore, the model can be feasible and applicable for simulation analysis and testing control algorithms.

Control of a boiler-turbine unit using MPC-based reference governors

An optimization-based scheme is proposed to improve safety and economical performance of a boiler-turbine system controlled by a set of interconnected PI controllers. The scheme, referred to as a reference governor, optimizes the references fed to the PI controllers in such a way that constraint satisfaction is enforced and tracking performance is improved. The proposed solution allows the plant operator to keep the existing PI control architecture and improve its performance by using an additional layer of control. The reference governor is based on optimizing the predicted future evolution of the closed-loop system, which consists of the plant and the inner PI controllers. Disturbance modeling is used to reject influence of the model-plant mismatch and to improve tracking performance. A case study is offered to demonstrate viability of the proposed approach with respect to energy savings and plant safety.

Control-oriented modeling and analysis of direct energy balance in coal-fired boiler-turbine unit

Direct energy balance (DEB) coordinated control scheme is widely used by field engineers in coal-fired power plants while attracting little attention in the academic community. This paper aims to derive a mathematical model that is suitable for DEB research. To balance the model’s fidelity and simplicity, the power plant is divided into three transformation modules and, using conservation laws, a dynamic model is developed to describe each module. Within reasonable assumptions, numerous module equations are combined to yield a 6th-order nonlinear model. Time constants of the model are identified based on Pareto optimization. Model accuracy is confirmed using field measurements from a 300 MW coal-fired power plant. Based on the linearized model, the merits of the DEB control structure are analyzed. It is confirmed that the DEB control is sufficient to fulfill the fundamental goals of power plant regulation. An illustration of performance improvement is given by introducing gain scheduling techniques to the DEB structure. The proposed model can provide groundwork for future development of advanced control algorithms under the DEB structure.

Improving the performance of a nonlinear boiler–turbine unit via bifurcation control of external disturbances: a comparison between sliding mode and feedback linearization control approaches

Boiler–turbine units may show quasiperiodic behavior due to the bifurcation occurrence in the presence of harmonic disturbances. In this study, a multi-input–multi-output nonlinear dynamic model of a boiler–turbine unit is considered. Drum pressure, electric output, and fluid density are the state variables and adjusted at the desired values by manipulation of the input variables. Control inputs are the valve positions for fuel, steam and feed-water flow rates. To improve the quasiperiodic behavior of the system and bifurcation control in tracking problem, two controllers are designed: feedback linearization control and nonlinear sliding mode control (SMC). The feedback linearization controller is designed based on the linearized dynamics. Dynamic response of the system in tracking of four different desired trajectories is examined. SMC controller acts more efficiently in suppression of harmonic perturbations and consequently bifurcation control. Appropriate tracking performance is observed for the drum pressure, electric output, fluid density and drum water level in both cases. Control efforts’ magnitudes in both controllers are almost similar. However, sliding mode controller vanishes the quasiperiodic solutions more successfully and leads to a more smooth response with less overshoots and less corresponding control efforts.

Nonlinear Boiler-Turbine Unit: Modelling and Robust Decentralized Control

Abstract Efficient control of a boiler-turbine unit is of great importance not only in power plants. In this paper, a linearized model is developed for a nonlinear Multi Input-Multi Output model (MIMO) of a utility boiler-turbine unit and a decentralized robust controller is designed. Drum pressure, generator electric output and drum water level (as the output variables) are controlled by manipulation of valves position for fuel, feedwater and steam flows. The proposed decentralized controller guarantees the prescribed maximum overshoot and settling time and is designed using Equivalent Subsystem Model method (ESM) including the interactions into subsystem model. The results are verified by simulation on nonlinear system model.

A dynamic model used for controller design of a coal fired once-through boiler-turbine unit

Supercritical OTB (once-through boiler) units with high steam temperature and pressure have been widely used in modern power plants due to their high cycle efficiency and less emissions. To ensure the effective operation of such power generation systems, it is necessary to build a model for the design of the overall control system. There are already detailed models of once-through boilers; however, their complexity prevents them from being applied in the controller design. This study describes a lumped parameter dynamic model that has a relatively low complexity while faithfully capturing the essential overall plant dynamics. The model structure was derived by fundamental physical laws utilizing reasonable simplifications and data analysis to avoid the phase transition position problem. Parameter identification for the model structure was completed using operational data from a 1000 MW ultra-supercritical OTB. The model was determined to be reasonable by comparison tests between computed data and measured data for both steady and dynamic states. The simplified model is verified to have appropriate fidelity in control system design to achieve effective and economic operation of the unit.

Optimization Techniques Applied to Boiler Turbine Unit

Objectives: Design and implementation of PI/PID controllers with parameter optimization using different techniques for MIMO systems. Methods: Biogeography Based Optimization based Proportional Integral Derivative (BBOPID) and investigating the robustness of the BBOPID technique applied to boiler turbine unit. Design of a Coordinated PID (CPID) Controller and tuning the CPID parameters using Particle Swarm Optimization (PSO), Bacteria Foraging (BF) and BBO techniques are discussed. Findings: The design of controller is done by using the performance index of Integral Square Error (ISE). Results show that BBO controller gives better performance for both servo and regulatory responses. Application: The electric power is generated using steam driven turbo generators, where the steam is produced by drum boilers as as practices base, reuses and stores the best practices.

Multivariable optimal control of an industrial nonlinear boiler–turbine unit

Performance control of a boiler–turbine unit is of great importance due to demands for the economical operations of power plants and environmental awareness. In this paper, an optimal control strategy is designed to achieve the desired performance of a boiler–turbine unit. A multivariable nonlinear model of a utility boiler–turbine unit is considered. By manipulation of valves position for the fuel, steam and feed-water flows; output variables including the drum pressure, electric output and fluid density (and consequently drum water level) are controlled. Performance measure of the problem is defined such that the control efforts are minimized while the tracking objectives are obtained. In development of the optimal control strategy, the “variation of extremal” approach is used as an effective tool to handle the nonlinear uncertain problems. Tracking performance of the system is investigated and compared for three cases; tracking from a specific operating point to another ‘near’, ‘far’ and ‘farther’ operating point (depending on the distance between the operating points, the qualitative phrases ‘near’, ‘far’ and farther’ are used). According to the results obtained, more control efforts are required for the tracking of farther operating points (generally). Also, it is investigated that the designed optimal controller guarantees the robust performance of the system in the presence of model parametric uncertainties.

An improved coordinated control strategy for boiler-turbine units supplemented by cold source flow adjustment

CCS (coordinated control strategy) is widely used for boiler-turbine units to change their steam turbine load. However, it is almost impossible to make a breakthrough in the load change performance just through CCS on account of the boiler's large delay. In order to accelerate the unit load response speed through the CSFA (cold source flow adjustment), the static and dynamic influence model of CSFA on the turbine power output is firstly set up in this paper. Then an improved strategy which combines CCS with CSFA control is brought forward to be used for the flexible load control. Another innovation of the improved strategy is to tie the output of CSFA controller to the measurement signal of the boiler controller, through which CSFA is used to quicken the turbine load response, the coal feeder rate to ensure the steady load accuracy, and the turbine governor valve to stabilize the main steam pressure. Furthermore, the condenser pressure will be recovered to its normal value for the next load dispatch use. Finally, simulation results confirm the effectiveness of the improved strategy compared to CCS, and moreover the extra coal consumption during the control process has been proved to be very small.