Stabilization of V94.2 Gas Turbine Using Intelligent Fuzzy Controller Optimized by the Genetic Algorithm

被引：0

作者：

Abadpour M. ^{[1
]}

Hamidi H. ^{[2
]}

机构：

[1] Department of Electrical Engineering, Islamic Azad University South of Tehran Branch, Tehran

[2] Department of Information Technology, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran

来源：

International Journal of Applied and Computational Mathematics | 2017年 / 3卷 / 4期

关键词：

Fuzzy control; Genetic algorithm; V94.2; turbine;

D O I：

10.1007/s40819-016-0276-2

中图分类号：

学科分类号：

摘要：

According to the crucial role of gas turbines in electricity production without significant harmful effects on the environment, this paper is aimed at the modeling and simulation of a particular type of these systems known as V94.2. Gas turbine is an instrument for power generation, which is capable of producing a vast amount of energy by considering its size and weight. Despite all the advantages and applications of gas turbines, the use of these systems is not free of difficulties because of their remote controls in such a way that it is estimated that about a quarter of turbine price is spent on its launching. To tackle this problem, a mathematical model has been proposed for V94.2 gas turbines as a result of the review of the pieces of research done on the modelling of gas turbines in the past few years and on the basis of Rowen model. In the following, the capability of fuzzy controllers has been used to ensure the system stability. In addition, an intelligent genetic algorithm has been added to the control structure in order to optimize the proposed control system as well as obviating the need of fuzzy control to the experts’ information about the system. The results of the simulation in MATLAB software clearly shows that the output variables of V94.2 gas turbine reach a specific situation and place after applying the inputs at the right time. © 2016, Springer India Pvt. Ltd.

引用

页码：2929 / 2942

页数：13

共 19 条

[1]

Baudoin S., Vechiu I., Camblong H., A review of voltage and frequency control strategies for islanded microgrid, System Theory, Control and Computing (ICSTCC), 2012 16Th International Conference On, pp. 1-5, (2012)

[2]

Oyedepo S.O., Fagbenle R.O., Adefila S.S., Adavbiele S.A., Performance evaluation and economic analysis of a gas turbine power plant in Nigeria, Energy Convers. Manag., 79, pp. 431-440, (2014)

[3]

Buonomano A., Calise F., d'Accadia M.D., Palombo A., Vicidomini M., Hybrid solid oxide fuel cells–gas turbine systems for combined heat and power: a review, Appl. Energy, 156, pp. 32-85, (2015)

[4]

Addabbo T., Cordovani O., Fort A., Mugnaini M., Vignoli V., Rocchi S., Gas turbine thermoelements availability analysis, Sensors, pp. 387-391, (2015)

[5]

Khorasani Nejad E., Hajabdollahi F., Hajabdollahi Z., Hajabdollahi H., Thermo-economic optimization of gas turbine power plant with details in intercooler, Heat Transf. Asian Res., 42, 8, pp. 704-723, (2013)

[6]

Yee S.K., Milanovic J.V., Hughes F.M., Overview and comparative analysis of gas turbine models for system stability studies, Power Syst. IEEE Trans., 23, 1, pp. 108-118, (2008)

[7]

Simani S., Fantuzzi C., Patton R.J., Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques, (2013)

[8]

Rowen W.I., Simplified mathematical representations of single shaft gas turbines in mechanical drive service, ASME 1992 International Gas Turbine and Aeroengine Congress and Exposition, (1992)

[9]

Borguet S., Leonard O., Comparison of adaptive filters for gas turbine performance monitoring, J. Comput. Appl. Math., 234, 7, pp. 2202-2212, (2010)

[10]

Tayarani-Bathaie S.S., Khorasani K., Fault detection and isolation of gas turbine engines using a bank of neural networks, J. Process Control, 36, pp. 22-41, (2015)

← 1 2 →