FUZZY LEARNING CONTROL OF ADVANCED SUPER-CONDUCTING MAGNETIC ENERGY STORAGE TO
IMPROVE TRANSIENT POWER SYSTEM STABILITY

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HAMDAOUI H.; SEMMAH A.; RAMDANI Y.; FELLAH M. K.

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Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE) Year:2004 | Volume:3 | Issue:2 Page(s): 95-102

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Information Journal Paper

Title

FUZZY LEARNING CONTROL OF ADVANCED SUPER-CONDUCTING MAGNETIC ENERGY STORAGE TO IMPROVE TRANSIENT POWER SYSTEM STABILITY

Author(s)

HAMDAOUI H. | SEMMAH A. | RAMDANI Y. | FELLAH M. K. | Issue Writer Certificate

Keywords

POWER SYSTEM STABILITY

CSI

ASMES

FUZZY LEARNING CONTROL

Abstract

This paper proposes an advanced structure of Super-conducting Magnetic Energy Storage using a PWM Current Source Inverter by adopting a robust method based on the fuzzy set theory for generate the modulation index and the shift angle, which allowed the active and reactive powers exchange control in the four quadrants. Two independent fuzzy controllers are assigned, one for the angular speed control and the other for the terminal voltage control.However, the fuzzy control methodology which has ever been reported has many problems, since structure and choosing of fuzzy rules, membership function and parameters in fuzzy controller are determined by trial and error depending on computer simulations and skilled person(s) intuition. In this paper, we introduce a learning control that is developed by synthesizing several basic ideas from fuzzy set and control theory, self-organizing control and conventional adaptive control. This provides the motivation for adaptive fuzzy control where the focus is on the automatic on-line synthesis and tuning of fuzzy controller parameters. Simulation results show that the proposed learning control is able to ensure the transient stability of power system under various fault conditions and significant disturbances.

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APA: Copy

HAMDAOUI, H., SEMMAH, A., RAMDANI, Y., & FELLAH, M. K.. (2004). FUZZY LEARNING CONTROL OF ADVANCED SUPER-CONDUCTING MAGNETIC ENERGY STORAGE TO IMPROVE TRANSIENT POWER SYSTEM STABILITY. IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE), 3(2), 95-102. SID. https://sid.ir/paper/283337/en

Vancouver: Copy

HAMDAOUI H., SEMMAH A., RAMDANI Y., FELLAH M. K.. FUZZY LEARNING CONTROL OF ADVANCED SUPER-CONDUCTING MAGNETIC ENERGY STORAGE TO IMPROVE TRANSIENT POWER SYSTEM STABILITY. IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE)[Internet]. 2004;3(2):95-102. Available from: https://sid.ir/paper/283337/en

IEEE: Copy

H. HAMDAOUI, A. SEMMAH, Y. RAMDANI, and M. K. FELLAH, “FUZZY LEARNING CONTROL OF ADVANCED SUPER-CONDUCTING MAGNETIC ENERGY STORAGE TO IMPROVE TRANSIENT POWER SYSTEM STABILITY,” IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE), vol. 3, no. 2, pp. 95–102, 2004, [Online]. Available: https://sid.ir/paper/283337/en

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