Analysis of the self-excited induction generator steady state performance using a new efficient algorithm

Kheldoun, Aissa; Refoufi, Larbi; Khodja, Djalal Eddine

doi:10.1016/j.epsr.2011.12.003

Cited by 42 publications

(26 citation statements)

References 8 publications

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“…The disadvantage of using the software built in functions is the requirement of the initial guess. Standalone programmed algorithms such as Genetic Algorithm, DIRECT Algorithm have been used by solving (1) as an unconstrained optimization problem where the upper and lower values are randomly selected beyond the specified ones in the problem constraints [14]. However the accuracy of the optimal solution is sensitive to the search space, meaning that wide search space results in long convergence and sometimes lower accuracy.…”

Section: B Optimisation-based Analysismentioning

confidence: 99%

“…By having these values and the saturation characteristic (A.1) of the machine under study (see appendix), the values of the magnetizing voltage (Vg) is computed. Finally the output parameters the stator current, the output voltage, the load current and the output power are calculated using (11)(12)(13)(14). In order to assess the accuracy of optimisation using Taguchi algorithm in solving the SEIG analysis, the external parameters affecting both the self-excitation process and the output performances of the induction generator are varied within loops.…”

Section: B Taguchi's Signal-to-noise Ratios (S/n)mentioning

confidence: 99%

“…DIRECT algorithm which does not suffer from this weakness has been successfully applied to minimise the admittance of the SEIG [14] to obtain the appropriate values of X m and F for different operating conditions: variable rotor speed, variable excitation capacitance and variable load impedance. DIRECT algorithm is a global optimisation algorithm which does not require any initial guess and guarantees to find the optimum solution for continuous function such as the induction generator admittance.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Application of new optimisation algorithm to self-excited induction generator analysis

Kheldoun

Refoufi

Eddine

2013

4th International Conference on Power Engineering, Energy and Electrical Drives

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The paper presents the application of the Taguchi's global optimisation algorithm to analyse the self-excited induction generator performances. The analysis is based essentially on finding the root of the equivalent circuit's admittance (or the impedance) being equated to zero. This equation has two unknowns the magnetizing reactance and the frequency. The two variables depend strongly on the equivalent circuit parameters and the external parameters which are the load, the excitation capacitance and the prime mover rotor speed. Previous work on the subject have used either gradient based or global search algorithms. In this work, a new global search technique is used to solve this equation. Besides its global search features, this optimization algorithm is superior in terms of accuracy and ease of implementation. A study of some simulations results carried out using Matlab software has been done to corroborate the above advantages.

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Section: B Optimisation-based Analysismentioning

confidence: 99%

Section: B Taguchi's Signal-to-noise Ratios (S/n)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Application of new optimisation algorithm to self-excited induction generator analysis

Kheldoun

Refoufi

Eddine

2013

4th International Conference on Power Engineering, Energy and Electrical Drives

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“…A smoothing inductor is connected in between the output side of semiconverter and dc microgrid to have the continuous dc grid current. In the case of SEIG, the output voltage and frequency vary with the driving speed and load [5][6][7][8][9][10][11][12][13][14]. For the present system, this variable voltage and variable frequency (VVVF) output from SEIG is fed to the three-phase semi-converter.…”

Section: Introductionmentioning

confidence: 99%

“…In such systems, squirrel-cage induction machines functioning as generators are being used due to their low cost, simple, robust construction and almost nil maintenance requirements [5][6][7][8][9][10][11][12]. This machine can be operated either as a grid-connected induction generator for supplying power to the grid or selfexcited induction generator (SEIG) for feeding power to the isolated loads.…”

Section: Introductionmentioning

confidence: 99%

Wind-driven SEIG supplying DC microgrid through a single-stage power converter

Nayanar

Kumaresan

Gounden

2016

Engineering Science and Technology, an International Journal

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a b s t r a c tNowadays, there is an increased emphasis on utilizing the renewable energy sources and selection of suitable power converters for supplying dc microgrid. Among the various renewable energy sources, wind energy stands first in terms of installed capacity. So, an attempt is made in this paper for supplying dc microgrid utilizing wind energy. A self-excited induction generator has been used in the proposed wind energy conversion system (WECS). A single-stage power converter, namely, semi-converter is connected between the SEIG and dc grid terminals for closed-loop control of the proposed system. A perturb and observe (P&O) based maximum power point tracking (MPPT) algorithm has been developed and implemented using a dsPIC30F4011 digital controller. In this MPPT algorithm, the firing angle of the converter is adjusted by continuously monitoring the dc grid current for a given wind velocity. For analyzing the proposed system, a MATLAB/Simulink model has been developed by selecting the various components starting from wind-turbine model to the power converter supplying dc microgrid. Successful working of the proposed WECS has also been shown through experimental results obtained on a prototype model developed in the laboratory.

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Voltage regulation approach to a self-excited induction generator: Theoretical study and experimental validation

Chermiti

Abid

Khedher

2016

Int. Trans. Electr. Energ. Syst.

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Summary This article describes an accurate steady‐state analysis of a stand‐alone 3‐phase self‐excited induction generator (SEIG). This analysis, based on the Newton‐Raphson algorithm, has shown that the system performance is greatly affected by the parameters related to the availability of primary energy, load variations, and excitation capacitor values. These parameters explain the stator voltage fluctuations and the output frequency decrease. To avoid any interruption of the excitation process and to ensure a good quality of the stand‐alone minigrid, a three‐phase voltage regulator (TPVR), based on switched capacitors, is proposed to keep the terminal SEIG voltage constant. The control algorithm and the regulation process are implemented using a microcontroller. The SEIG‐TPVR is experimentally developed, and a variable capacitor bank is constructed. The experimental investigations on a 1.5‐kW induction machine confirm the efficiency of the whole suggested system.

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Analysis of the self-excited induction generator steady state performance using a new efficient algorithm

Cited by 42 publications

References 8 publications

Application of new optimisation algorithm to self-excited induction generator analysis

Application of new optimisation algorithm to self-excited induction generator analysis

Wind-driven SEIG supplying DC microgrid through a single-stage power converter

Voltage regulation approach to a self-excited induction generator: Theoretical study and experimental validation

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