The Use of the Åström-Bell Model for the Design of Drum Level Controllers in Power Plant Boilers

Lu, Chris Xiaoxuan; Rees, N.W.; Donaldson, S.C.

doi:10.3182/20050703-6-cz-1902.01752

Cited by 11 publications

(5 citation statements)

References 4 publications

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“…For disturbance rejection also it turned out be effective. Lu et al [17] used Astrom and Bell model for the design of drum level controllers in power plant boilers. Yang et al [18] proposed a new approach for water level control in power station based on an internal model control using neural networks.…”

Section: Introductionmentioning

confidence: 99%

Boilers Optimal Control for Maximum Load Change Rate

Elshafei

Habib

Al-Zaharnah

et al. 2014

Journal of Energy Resources Technology

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In many cogeneration systems, one or more boilers are used in hot standby to meet the plant demand of steam in case of failure or upset in the cogeneration unit. Such boilers need to quickly respond to sudden and large steam load changes. However, fast changes in the firing rate cause transient changes in both the drum-boiler steam pressure and drum level, in addition to the potential of developing of thermal stresses in the walls of steam risers. A genetic algorithm (GA) based optimization scheme is proposed for tuning the conventional boiler control loops to maximize the ability of the boiler to respond to large steam demand while keeping the fluctuations in pressure, drum level, and feed rate within acceptable operation limits. A nonlinear model for an actual boiler is first built, validated, and then, it is used to demonstrate the performance of the boiler with the proposed control loop optimization.

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Section: Introductionmentioning

confidence: 99%

Boilers Optimal Control for Maximum Load Change Rate

Elshafei

Habib

Al-Zaharnah

et al. 2014

Journal of Energy Resources Technology

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“…Regarding drum boilers, note that the water level control is a severe issue due to the so called shrink-and-swell effect. Several works propose advanced strategies, e.g., [4], [5] and references herein. [4] proposes a Dynamic Matrix Control (DMC) approach based on step-response models to describe system dynamics.…”

Section: State Of the Artmentioning

confidence: 99%

“…The identified static map ( 21) is presented for different values of , uexHex in solid lines. Markers show the steady-state data of the nonlinear model (5).…”

Section: The Boiler High-level Hybrid Modelmentioning

confidence: 99%

An optimal hierarchical control scheme for smart generation units: An application to combined steam and electricity generation

Spinelli

Farina

Ballarino

2020

Journal of Process Control

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Optimal management of thermal and energy grids with fluctuating demand and prices requires to orchestrate the generation units (GU) among all their operating modes. A hierarchical approach is proposed to control coupled energy nonlinear systems. The high level hybrid optimization defines the unit commitment, with the optimal transition strategy, and best production profiles. The low level dynamic model predictive control (MPC), receiving the set-points from the upper layer, safely governs the systems considering process constraints. To enhance the overall efficiency of the system, a method to optimal start-up the GU is here presented: a linear parameter varying MPC computes the optimal trajectory in closed-loop by iteratively linearising the system along the previous optimal solution. The introduction of an intermediate equilibrium state as additional decision variable permits the reduction of the optimization horizon,while a terminal cost term steers the system to the target set-point. Simulation results show the effectiveness of the proposed approach.

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“…The steam boiler plant is a very critical plant in all industries involved in the production of steam for use in a variety of industrial applications [12,13,14,15,16,17,18]. In a coal fired power plant, the steam boiler is basically a group of energy conversion equipment that converts chemical energy from fossil fuels like coal, fuel oil or gas into steam energy which will then be used as a source of mechanical energy for driving the turbines that turn the generators.…”

Section: Introductionmentioning

confidence: 99%