Stand alone self-excited induction generator with reduced excitation capacitors at fixed speed

Trapp, J. G.; Parizzi, Jocemar Biasi; Farret, Felix A.; Longo, Adriano J.

doi:10.1109/cobep.2011.6085328

Cited by 7 publications

(8 citation statements)

References 6 publications

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“…Q m = 3U m I m = 3U m ωCU m = 2U m , 2π f C = 6π f CU m , (10) In no load case, generator needs reactive power for self-excitation only, but in loading case, generator needs additional reactive power to provide the required of induction load that connected with it so we find [12]:…”

Section: Self-excitation Induction Generatormentioning

confidence: 99%

“…# : the ratio between no load current and nominal current for generator . Notes from the equation 13 that the necessary capacity for excitation related to several factors, it is proportional to the power of generator P t , and inversely with both the frequency (speed ) and a square of voltage , [4], and proportional to tan z & tan y ( inversely with cos z & cos y ),this means that the power of capacitors that used with induction generators increases with increasing its power and fall down with falling down both voltage and frequency [2] [12].…”

Section: Self-excitation Induction Generatormentioning

confidence: 99%

“…The most important advantages in induction generators are simple structure, high Reliability, high efficiency ,and ability to work on the changing speed of the wind turbine [8] [12] [14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Study of Induction Generators Performance of Two-Speed Used in Standalone Wind Turbines

Al-khamis¹,

safe²

2016

IJESG

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Recent interest in renewable energy sources is growing as a resource substitute for conventional energy and this led to increased interest in electric power can be obtained from the wind energy. With the rapid development in electrical generators used in wind turbines, induction generators have proven quality among the different types of electric generators used in this field. Based on that research aims to study the behavior of squirrel cage induction generator(two-speed) when linked with a wind turbine and study of using feasibility in this field. To achieve this purpose theoretical and practical study for induction generator two-speed were completed. Theoretical study contains a review of principles of operation of the machine , circuit equivalent and math equations, but practical study has been fulfilled on a laboratory model for two-speed induction generator driven by DC motor with variable speed. This study has been fulfilled when induction generator operates on both of speed and set speed at which it move from working as a motor to work as a generator for different values of the excitation capacitors, and relationship between voltage of generator and speed is identified at different degrees of excitation.

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Section: Self-excitation Induction Generatormentioning

confidence: 99%

Section: Self-excitation Induction Generatormentioning

confidence: 99%

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Study of Induction Generators Performance of Two-Speed Used in Standalone Wind Turbines

Al-khamis¹,

safe²

2016

IJESG

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“…The previous Eqs. (7)(8)(9)(10)(11)(12)(13)(14)(15)(16) are used to develop a dynamic model of three phase SEIG using MatLab/Simulink.…”

Section: √ (12)mentioning

confidence: 99%

“…Poor frequency regulation due to the SEIG's loading appears as another serious problem standing in the operation of SEIG. Many researchers have been attempted to solve this problem using the development of power electronics [11][12][13][14][15]. They suggested to convert the terminal voltage of the induction generator from AC to DC voltage using rectifiers and then from DC to AC by using PWM inverters with certain frequency.…”

Section: Introductionmentioning

confidence: 99%

Optimal Performance of Self Excited Induction Generator Using Teaching Learning-Based Optimization Algorithm and Static Var Compensator

Elkholy

2016

ERJ. Engineering Research Journal

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The paper presents an application of Teaching Learning-Based Optimization (TLBO) algorithm to improve the performance of self-excited induction generators (SEIG). Two control methods of SEIG have been studied. The first method, the TLBO algorithm is applied to generate the optimal capacitance to maintain rated voltage with constant prime mover speed. The drawback of this method is the generator frequency decreases with load and to overcome this disadvantage, the other control method is proposed. In the proposed method, the TLBO is used to obtain optimal capacitance and prime mover speed to have rated load voltage and frequency. The Static VAR Compensator (SVC) of fixed capacitor and controlled reactor is used to control the reactive power. The parameters of SVC are obtained by using TLBO algorithm. The performance of the SEIG at different loads and prime mover speeds using TLBO algorithm is realized. A whole system of three phase induction generator and SVC is established under MatLab/Simulink environment. The performance of the SEIG is demonstrated on two different ratings (i.e. 10 hp and 2hp). An experimental setup is built-up using a 2 hp induction motor to confirm the theoretical analysis. Good agreement between results confirms and signifies the viability of the proposed TLBO-based methodology.

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Steady state and dynamic performance of self-excited induction generator using FACTS controller and teaching learning-based optimization algorithm

Elkholy

2018

COMPEL

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Purpose The paper aims to present an application of teaching learning-based optimization (TLBO) algorithm and static Var compensator (SVC) to improve the steady state and dynamic performance of self-excited induction generators (SEIG). Design/methodology/approach The TLBO algorithm is applied to generate the optimal capacitance to maintain rated voltage with different types of prime mover. For a constant speed prime mover, the TLBO algorithm attains the optimal capacitance to have rated load voltage at different loading conditions. In the case of variable speed prime mover, the TLBO methodology is used to obtain the optimal capacitance and prime mover speed to have rated load voltage and frequency. The SVC of fixed capacitor and controlled reactor is used to have a fine tune in capacitance value and control the reactive power. The parameters of SVC are obtained using the TLBO algorithm. Findings The whole system of three-phase induction generator and SVC are established under MatLab/Simulink environment. The performance of the SEIG is demonstrated on two different ratings (i.e. 7.5 kW and 1.5 kW) using the TLBO algorithm and SVC. An experimental setup is built-up using a 1.5 kW three-phase induction machine to confirm the theoretical analysis. The TLBO results are matched with other meta heuristic optimization techniques. Originality/value The paper presents an application of the meta-heuristic algorithms and SVC to analysis the steady state and dynamic performance of SEIG with optimal performance.

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Stand alone self-excited induction generator with reduced excitation capacitors at fixed speed

Cited by 7 publications

References 6 publications

Study of Induction Generators Performance of Two-Speed Used in Standalone Wind Turbines

Study of Induction Generators Performance of Two-Speed Used in Standalone Wind Turbines

Optimal Performance of Self Excited Induction Generator Using Teaching Learning-Based Optimization Algorithm and Static Var Compensator

Steady state and dynamic performance of self-excited induction generator using FACTS controller and teaching learning-based optimization algorithm

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