Modelling and Simulation of Power Generation Plants

Ordys, Andrzej; Pike, Andrew; Johnson, Michael; Katebi, Reza; Grimble, M.J.

doi:10.1007/978-1-4471-2114-5

Cited by 108 publications

(103 citation statements)

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“…In this paper, the boiler model described in [11] is modified by replacing the drum and the riser models by a simple fourth order non-linear drum model [17] that can capture much of the system dynamic such as Shrink and Swell phenomena.…”

Section: Boiler Modelmentioning

confidence: 99%

“…In this paper, the drum model was simulated using Skegton power plant data as presented in [11]. Due to lack of data availability, some parameters 0 (, sd VT and K ) were assumed by scaling down the values from [17].…”

Section: Boiler Modelmentioning

confidence: 99%

“…Due to lack of data availability, some parameters 0 (, sd VT and K ) were assumed by scaling down the values from [17]. The total drum volume is calculated from [11] as follows:…”

Section: Boiler Modelmentioning

confidence: 99%

“…Reference [11] describes a moderately complicated boiler model for CCPP that is suitable for model based control. It consists of the following subsystems: furnace, risers, drum, superheater, reheater and economizer.…”

Section: Introductionmentioning

confidence: 99%

“…Output constraints are also included in solving the optimization problem. Regarding the CCPP modelling, the boiler model described in [11] is modified to include the shrink and swell dynamics. This model is integrated with Gas and Steam turbines models to create a complete CCPP simulator in Matlab/Simulink environment.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Modeling and Supervisory Control Design for a Combined Cycle Power Plant

Abokhatwa¹,

Katebi²

2012

Software Engineering / 781: Control Applications

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The traditional control strategy based on PID controllers may be unsatisfactory when dealing with processes with large time delay and constraints. This paper presents a supervisory model based constrained predictive controller (MPC) for a combined cycle power plant (CCPP). First, a non-linear dynamic model of CCPP using the laws of physics was proposed. Then, the supervisory control using the linear constrained MPC method was designed to tune the performance of the PID controllers by including output constraints and manipulating the set points. This scheme showed excellent tracking and disturbance rejection results and improved performance compared with a stand-alone PID controller's scheme. KEY WORDSCombined cycle power plant, PID Control, Linearization, Supervisory Model Predictive Control.

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Section: Boiler Modelmentioning

confidence: 99%

Section: Boiler Modelmentioning

confidence: 99%

“…Due to lack of data availability, some parameters 0 (, sd VT and K ) were assumed by scaling down the values from [17]. The total drum volume is calculated from [11] as follows:…”

Section: Boiler Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Modeling and Supervisory Control Design for a Combined Cycle Power Plant

Abokhatwa¹,

Katebi²

2012

Software Engineering / 781: Control Applications

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Adaptive hybrid predictive control for a combined cycle power plant optimization

Sáez

Zúñiga

Cipriano

2007

Adaptive Control & Signal

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The design and development of an adaptive hybrid predictive controller for the optimization of a real combined cycle power plant (CCPP) are presented. The real plant is modeled as a hybrid system, i.e. logical conditions and dynamic behavior are used in one single modeling framework. Start modes, minimum up/down times and other logical features are represented using mixed integer equations, and dynamic behavior is represented using special linear models: adaptive fuzzy models. This approach allows the tackling of special non-linear characteristics, such as ambient temperature dependence on electrical power production (combined cycle) and gas exhaust temperature (gas turbine) properly to fit into a mixed integer dynamic (MLD) model. After defining the MLD model, an adaptive predictive control strategy is developed in order to economically optimize the operation of a real CCPP of the Central Interconnected System in Chile. The economic results obtained by simulation tests provide a 3% fuel consumption saving compared to conventional strategies at regulatory level.

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Dynamic behavior of a distributed incinerator power system under output power variation

Chen

Liu

et al. 2014

Int J Numerical Modelling

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SUMMARYIn Taiwan, the sales revenues of power generation from incinerator power plants with heat recovery power generation sold to the power company were up to NT$4.5bn, making the incinerator power generation play an important role in reduction of impact on environment and substitution of energy in power generation. Studying the dynamic behavior of incinerator power systems under output power variation is thus an essential task for the scheduling, operation, and expansion of incinerator power plants, such as, for cooperating with a scheduling program based on pricing signals to capture energy trading timing economically and to operate the incinerator power system securely. Although there are many studies on incinerator power generation, they seldom discuss the power generation system characteristics. In this paper, mathematical dynamic models for a distributed incinerator power system were derived and implemented using Matlab/Simulink, and dynamic characteristics of the system were further simulated and discussed under two operating modes: increment and decrement of power generation. These developed models can provide dynamic characteristics for these two modes, serving as an important analytic tool for cooperating with a scheduling program based on pricing signals to capture energy trading timing economically and to operate the incinerator power system securely. Copyright

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Modelling and Simulation of Power Generation Plants

Cited by 108 publications

References 0 publications

Modeling and Supervisory Control Design for a Combined Cycle Power Plant

Modeling and Supervisory Control Design for a Combined Cycle Power Plant

Adaptive hybrid predictive control for a combined cycle power plant optimization

Dynamic behavior of a distributed incinerator power system under output power variation

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