Model reduction of transformer detailed R-C-L-M model using the imperialist competitive algorithm

Rashtchi, Vahid; Rahimpour, Ebrahim; Shahrouzi, Hamid

doi:10.1049/iet-epa.2011.0331

Cited by 22 publications

(19 citation statements)

References 18 publications

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“…During competition, weaker empires are neglected and positions are collapsed and positions are updated. This may lead to converge to a state with one empire [39][40][41][42][43][44][45][46][47][48][49].…”

Section: Imperialistic Competitive Algorithm (Ica)mentioning

confidence: 99%

“…Dynamic Programming is good for a variety of sizes, but more complex hence the computation time more [27]. A new algorithm called an imperialistic competitive algorithm (ICA) inspired by imperialistic competition, which causes the colonies to converge to global minimum cost function [39][40][41][42][43][44][45][46][47][48][49][50] has been attempted in this research…”

Section: Introductionmentioning

confidence: 99%

“…Then the imperialistic competition begins to obtain the global optimal solution. ICA has been implemented in solving various optimization problems like DG planning [39], template matching [40], optimal design of plate-fin heat exchangers [41] electromagnetic problems [42], power system stabilizer design [43], linear induction motor design [44], economic dispatch [45] and model reduction of a detailed transformer model [46]. Recently Imperialist Competitive algorithm [47] has also been implemented for solving unit commitment with a thermal unit alone.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Imperialistic Competitive Algorithm for Unit Commitment with Wind Generation

Sudhakar¹,

Balasubramanian²,

Padmanaban³

2018

IJIES

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Abstract:The integration of wind power to the grid is essential to meet the growing power demand and possess a challenge to unit commitment to meet the load demand at low cost for scheduling the generating units. A new imperialistic competitive algorithm (ICA) has been developed for the above mentioned unit commitment problem for solving deterministic and stochastic condition. This imperialistic competitive algorithm has been developed with constraints, including generation limits, start up and shut down cost, minimum up and downtime along with ramp constraint. The ICA has been studied initially on the 10 units 24 hour system and 40 units 24 hour system for the deterministic load. Later, a wind generator has been added to the 10 units 24 hour system with wind data for 24 hours and the results are compared with genetic algorithm (GA), particle swarm optimization (PSO), hybrid particle swarm optimisation (HPSO), shuffled frog leaping algorithm (SFLA), invasive weed optimization (IWO). The comparison result is presented in this paper and it shows that the ICA gives optimized fuel cost of $482246.2 which is less than the LR, GA, BFOA, SFLA, IWO for stochastic unit commitment.

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Section: Imperialistic Competitive Algorithm (Ica)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Novel Imperialistic Competitive Algorithm for Unit Commitment with Wind Generation

Sudhakar¹,

Balasubramanian²,

Padmanaban³

2018

IJIES

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“…Some evolutionary optimization algorithms like GA, ICA, honey bee algorithm [10]- [11] are presented for optimization of complicated fitness functions.…”

Section: Pso Algorithm Proceduresmentioning

confidence: 99%

Using of Particle Swarm Optimization for Loss Minimization of Vector-controlled Induction Motors

Rashtchi¹,

Bizhani²

2015

ujeee

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This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a tradeoff between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

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“…Therefore, it is very essential to identify any minor winding deformation as soon as possible and take a proper asset management decision to avoid disastrous failures including environmental hazards due to oil spillage. Winding deformation has various configuration moods such as spiral tightening, conductor tilting, radial buckling and collapse of the winding end supports and it is hard to identify these types of internal faults using conventional testing methods [3].One of the powerful diagnostic techniques in identifying internal faults of power transformers is the frequency response analysis (FRA) test. Since power transformer components including windings, core and insulation can be represented by equivalent electrical parameters comprising resistors, capacitors, and self / mutual inductances, the value of these electrical parameters will be altered for any mechanical fault within the power transformer and hence the frequency response of the winding will change accordingly [4].…”

mentioning

confidence: 99%

Impact of axial displacement on power transformer FRA signature

Hashemnia

Abu-Siada

Islam

2013

2013 IEEE Power &Amp; Energy Society General Meeting

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Abstract-Frequency response analysis (FRA) is gaining global popularity in detecting power transformer winding movement and core deformation due to the development of FRA test equipment. However, because FRA relies on graphical analysis, interpretation of its signatures is still a very specialized area that calls for skillful personnel to detect the sort and likely place of the fault as so far, there is no reliable standard code for FRA signature classification and quantification. This paper investigates the impact of transformer winding axial displacement on its FRA signature as a step toward the establishment of reliable codes for FRA interpretation. In this context a detailed model for a single-phase transformer is simulated using 3D finite element analysis to emulate a close to real transformer. The impact of axial displacement on the electrical distributed parameters model that are calculated based on the transformer physical dimension is examined to investigate how model's parameters including inductance and capacitance matrices change when axial displacement takes place within a power transformer.

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Model reduction of transformer detailed R-C-L-M model using the imperialist competitive algorithm

Cited by 22 publications

References 18 publications

A Novel Imperialistic Competitive Algorithm for Unit Commitment with Wind Generation

A Novel Imperialistic Competitive Algorithm for Unit Commitment with Wind Generation

Using of Particle Swarm Optimization for Loss Minimization of Vector-controlled Induction Motors

Impact of axial displacement on power transformer FRA signature

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