Adaptive model predictive control design for the speed and temperature control of a V94.2 gas turbine unit in a combined cycle power plant

Haji, Vahab Haji; Fekih, Afef; Monje, Concepción A.; Asfestani, Ramin Fakhri

doi:10.1016/j.energy.2020.118259

Cited by 21 publications

(6 citation statements)

References 18 publications

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“…Equations ( 12) and (13) show lines in the parameter plane. [32][33][34][35] The solution given in (18) is the intersection of these lines. These lines are parallel to each other for singular frequency (w = w s ).…”

Section: Determination Of Stable Region For Pi Type Controller Using ...mentioning

confidence: 99%

“…A real root along this line crosses the imaginary axis. In order for the solution given in (18) to exist, the determinant of Ω(w) must be non-zero. On the other hand, this determinant is equal to zero when w = 0 or N 2 re (w) + N 2 im (w) = 0.…”

Section: Determination Of Stable Region For Pi Type Controller Using ...mentioning

confidence: 99%

“…16 Fuzzy logic control method was proposed for speed control in natural gas turbine power plants by Ahmet et al 17 Haji et al proposed the adaptive model for the gas turbine power plant predictive control method. 18 Generally, conventional controllers such as PID and PI allow the system to respond fastly control design in natural gas combined cycle power plants. Eslami et al 19 proposed an intelligent method, based on the artificial bee colony (ABC) algorithm, to design an optimal PID-based low-pass filter for a gas turbine power plant to improve its stability.…”

Section: Introductionmentioning

confidence: 99%

“…Stanescu et al conducted on the control of the temperature of compressed air used in the combustion chamber in gas turbine 16 . Fuzzy logic control method was proposed for speed control in natural gas turbine power plants by Ahmet et al 17 Haji et al proposed the adaptive model for the gas turbine power plant predictive control method 18 . Generally, conventional controllers such as PID and PI allow the system to respond fastly control design in natural gas combined cycle power plants.…”

Section: Introductionmentioning

confidence: 99%

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PI control based on parameter space approach supported metaheuristic optimization algorithms and ANFIS in a natural gas combined cycle power plant

Bayhan

Tiryaki

2021

Optim Control Appl Methods

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In this article, proportional‐integral (PI) control to ensure stable operation of a steam turbine in a natural gas combined cycle power plant is investigated, since active power control is very important due to the constantly changing power flow differences between supply and demand in power systems. For this purpose, an approach combining stability and optimization in PI control of a steam turbine in a natural gas combined cycle power plant is proposed. First, the regions of the PI controller, which will stabilize this power plant system in closed loop, are obtained by parameter space approach method. In the next step of this article, it is aimed to find the best parameter values of the PI controller, which stabilizes the system in the parameter space, with artificial intelligence‐based control and metaheuristic optimization. Through parameter space approach, the proposed optimization algorithms limit the search space to a stable region. The controller parameters are examined with Particle Swarm Optimization based PI, artificial bee colony based PI, genetic algorithm based PI, gray wolf optimization based PI, equilibrium optimization based PI, atom search optimization based PI, coronavirus herd immunity optimization based PI, and adaptive neuro‐fuzzy inference system based PI (ANFIS‐PI) algorithms. The optimized PI controller parameters are applied to the system model, and the transient responses performances of the system output signals are compared. Comparison results of all these methods based on parameter space approach that guarantee stability for this power plant system are presented. According to the results, ANFIS‐ PI controller is better than other methods.

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Section: Determination Of Stable Region For Pi Type Controller Using ...mentioning

confidence: 99%

Section: Determination Of Stable Region For Pi Type Controller Using ...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

PI control based on parameter space approach supported metaheuristic optimization algorithms and ANFIS in a natural gas combined cycle power plant

Bayhan

Tiryaki

2021

Optim Control Appl Methods

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“…Testing experience and parameter identification using the operational data from the power plant site have been discussed in References 18‐21. In Reference 22, an adaptive model predictive control design and online parameter estimation for a gas turbine have been proposed. The main control loops of the gas turbine, including load and speed controller, have been taken into account.…”

Section: Introductionmentioning

confidence: 99%

A new method to identify synchronous generator and turbine‐governor parameters of a gas unit using a closed‐loop model

Zaker

Khalili

Rabieyan

et al. 2021

Int Trans Electr Energ Syst

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Summary In this paper, an efficient three‐stage algorithm for identifying the turbine‐governor (TG) and synchronous generator (SG) parameters is proposed. Instead of considering approximate models, precise models of the TG and SG are used. In the proposed approach, d‐q axes parameters of SG, mechanical parameters of SG, and TG model parameters are estimated. For the TG model, all the main control loops are carefully modeled with respect to the real‐world system. Moreover, the robustness of the governor is enhanced by employing an anti‐windup configuration for the load‐speed controller. The well‐known seventh‐order SG model is also used. The accuracy of the model and effectiveness of the parameter identification procedure is verified by experimental data. The results show satisfactory numbers for the selected performance index in various operating points when different controllers are in effect.

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Identification of twin-shaft gas turbine based on hybrid decoupled state multiple model approach

et al. 2023

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The work presented in this paper focuses on presenting an hybrid identification method for a nonlinear dynamic gas turbine, from a real time input and outputs data exploitation, with the fuel flow as the input and the rotational speed of high pressure and low pressure turbine as outputs. The multi model, which are in the form of a weighted combination of local linear state space models, offer an interesting alternative of the nonlinear models because it takes into account a several operating modes. The models are identified with the help of decoupled models using a hybrid approach between parametric estimation using artificial intelligence algorithms.

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Adaptive model predictive control design for the speed and temperature control of a V94.2 gas turbine unit in a combined cycle power plant

Cited by 21 publications

References 18 publications

PI control based on parameter space approach supported metaheuristic optimization algorithms and ANFIS in a natural gas combined cycle power plant

PI control based on parameter space approach supported metaheuristic optimization algorithms and ANFIS in a natural gas combined cycle power plant

A new method to identify synchronous generator and turbine‐governor parameters of a gas unit using a closed‐loop model

Identification of twin-shaft gas turbine based on hybrid decoupled state multiple model approach

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