Adaptive voltage regulation of self excited induction generator using FACTS controllers. (1st January 2014)

• Record Type: Journal Article
• Authors: Mosaad, Mohamed I.; Salem, Fawzan
• Is Part Of: International journal of industrial electronics and drives. Volume 1:Number 4(2014)
• Page Start: 219
• Page End: 226
• Publication Date: 2014-01-01
• Subjects: self excited induction generator -- SEIG -- flexible AC transmission systems -- FACTS -- static VAR compensator -- SVC -- adaptive neuro-fuzzy inference systems -- ANFIS -- artificial neural network -- ANN; Electrical engineering -- Periodicals; Electric driving -- Periodicals; 621.381
• Languages: English
• ISSNs: 1757-3874

Abstract

This paper introduces an adaptive terminal voltage regulation of a standalone self excited induction generator using flexible AC transmission systems (FACTS). FACTS in the form of static VAR compensator (SVC) is introduced. SVC is used to regulate the terminal voltage of self excited induction generator-based (SEIG) wind generator working with variable speed and load. Since, the wind generator operates over a wide range of operating conditions; the terminal voltage of the induction generator is not regulated. This terminal voltage is controlled by adapting the value of the excitation capacitance of SVC using artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS). Changing the excitation capacitance is performed by controlling the firing angle of SVC under different operating conditions to control the terminal voltage. A mathematical model of SEIG with variable load and speed along with SVC is developed and simulated in MATLAB to get the excitation capacitance required for voltage control. Simulation results are used to train both ANN and ANFIS for on-line prediction of the suitable firing angles required to control the terminal voltage of the system under these operating conditions. Results signify the supremacy of ANFIS over ANN in terms of performance measures.