Fuzzy Predictive Control for Power Plants

Cipriano, Aldo

doi:10.1007/978-1-84628-469-4_19

Cited by 6 publications

(3 citation statements)

References 36 publications

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“…Much attention in [15,16] is paid to control based on fuzzy logic, namely, a control method for regulating power and enthalpy in the boiler of a 765 MW coal-ired thermal power plant is presented, and fuzzy boiler power control by a steam regulating valve.…”

Section: Related Workmentioning

confidence: 99%

The Coal Quality CICS that Increases the Wear Resistance of Heat Exchanger Tubes

Grishyn,

Beglov

2024

JAMRIS

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The paper discusses the threat of decommissioning of the thermal power plant (TPP) heat exchanger tubes because of erosion and develops a computer-integrated control system (COAL QUALITY CICS THAT INCREASES THE WEAR RESISTANCE OF HEAT EXCHANGER TUBES) for the process of distribution of steam coal flows with different indicators of abrasive materials content, which is based on fuzzy logic. The problem of rapid decommissioning of TPP heat exchanger, particularly abrasive damage to furnace screen tubes, economizer, superheater, etc. This may indicate a discrepancy between the expected fuel ash content and the actual one, as well as a high content of abrasive impurities in steam coal. The work aims to develop a CICS of the wear resistance of the heat exchange surface of a steam boiler of a coal-fired power plant by measuring and fuzzy control of the content of abrasive impurities in steam coal. The problems of damage to the equipment of the TPP boiler are investigated and a system for controlling the wear resistance of the surface by automatic fuzzy control of the quality of coal is developed. In order to investigate the effectiveness of the proposed fuzzy controller, the results were investigated in a specific example, in particular, during coal preparation and combustion in the furnace of a thermal power plant. The model results confirm the feasibility of the fuzzy control method for the system with different coal quality parameters.

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Section: Related Workmentioning

confidence: 99%

The Coal Quality CICS that Increases the Wear Resistance of Heat Exchanger Tubes

Grishyn,

Beglov

2024

JAMRIS

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“…The control structure adopted in these works is of extreme interest. For instance, Cipriano [170] discussed implementation of fuzzy predictive control for power plants using nonlinear models based on fuzzy expert systems, and using fuzzy logic to characterize the objective function and the constraints. Other studies have been devoted to the adoption of solutions based on fuzzy logic (Ben Abdennour and Lee, 1996) [171], hybrid supervision systems (Garcia et al, 1995) [172], and genetic algorithms (Dimeo and Lee, 1994) [173].…”

Section: B Control Strategiesmentioning

confidence: 99%

A General Overview of Combined Cycle Gas Turbine Plants

Talah¹,

Bentarzi

2023

AJSS

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The Combined Cycle Gas Turbines (CCGT) has encountered a large diffusion over the last decades. Different researchers have focused on performance evaluation of CCGT through mathematical modeling techniques. Hence, there are some important factors which should be respected while modeling the CCGT. These factors include type of different components of the CCGT system, their configuration, the modeling methods, and the purpose of the modeling, the type and structure of the control system and the simulation objectives. Hence, a brief overview about CCGT design and technologies, mathematical modeling, simulation tools and methods are presented in this paper.

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“…Suarez et al (2006) developed a new predictive control scheme based on neural networks to linearize nonlinear dynamical systems. Cipriano (2006) discussed implementation of fuzzy predictive control for power plants using nonlinear models based on fuzzy expert systems, and using fuzzy logic to characterize the objective function and the constraints. An NMPC for frequency and temperature control of a heavy-duty industrial power plant GT was developed by Kim et al (2013).…”

Section: Black-box Modelsmentioning

confidence: 99%

Design of conventional and neural network based controllers for a single-shaft gas turbine

Asgari

Jegarkandi

Chen

et al. 2017

AEAT

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Purpose -The purpose of this paper is to develop and compare conventional and neural network based controllers for gas turbines.Design/methodology/approach -Design of two different controllers is considered. These controllers consist of a NARMA-L2 which is an ANN-based nonlinear autoregressive moving average (NARMA) controller with feedback linearization, and a conventional proportional-integrator-derivative (PID) controller for a low-power aero gas turbine.They are briefly described and their parameters are adjusted and tuned in Simulink-MATLAB environment according to the requirement of the gas turbine system and the control objectives. For this purpose, Simulink and neural network based modelling is employed. Performances of the controllers are explored and compared on the base of design criteria and performance indices.Findings -It is shown that NARMA-L2, as a neural network based controller, has a superior performance to the PID controller.Practical implications -Using artificial intelligence in gas turbine control systems.Originality/value -Providing a novel methodology for control of gas turbines.

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Fuzzy Predictive Control for Power Plants

Cited by 6 publications

References 36 publications

The Coal Quality CICS that Increases the Wear Resistance of Heat Exchanger Tubes

The Coal Quality CICS that Increases the Wear Resistance of Heat Exchanger Tubes

A General Overview of Combined Cycle Gas Turbine Plants

Design of conventional and neural network based controllers for a single-shaft gas turbine

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