A power system simulation tool based on Simulink

Dessaint, L.-A.; Al‐Haddad, Kamal; Le‐Huy, Hoang; Sybille, G.; Brunelle, P.

doi:10.1109/41.808019

Cited by 83 publications

(26 citation statements)

References 3 publications

(2 reference statements)

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“…The model includes start up characteristics and emissions although it is not clear how detailed the model is 5 .…”

Section: Original Research Papermentioning

confidence: 99%

Fuel Cell Vehicle Simulation – Part 1: Benchmarking Available Fuel Cell Vehicle Simulation Tools

Hauer¹,

Moore

2003

Fuel Cells

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Fuel cell vehicle simulation is one method for systematic and fast investigation of the different vehicle options (fuel choice, hybridization, reformer technologies). However, a sufficient modeling program, capable of modeling the different design options, is not available today. Modern simulation programs should be capable of serving as tools for analysis as well as development. Shortfalls of the existing programs, initially developed for internal combustion engine hybrid vehicles, are: (i)Insufficient modeling of transient characteristics; (ii) Insufficient modeling of the fuel cells system; (iii) Insufficient modeling of advanced hybrid systems; (iv) Employment of a non‐causal (backwards looking) structure; (v) Significant shortcomings in the area of controls.In the area of analysis, a modeling tool for fuel cell vehicles needs to address the transient dynamic interaction between the electric drive train and the fuel cell system. Especially for vehicles with slow responding on‐board fuel processor, this interaction is very different from the interaction between a battery (as power source) and an electric drive train in an electric vehicle design. Non‐transient modeling leads to inaccurate predictions of vehicle performance and fuel consumption. When applied in the area of development, the existing programs do not support the employment of newer techniques, such as rapid prototyping. This is because the program structure merges control algorithms and component models, or different control algorithms (from different components) are lumped together in one single control block and not assigned to individual components as they are in real vehicles. In both cases, the transfer of control algorithms from the model into existing hardware is not possible. This paper is the first part of a three part series and benchmarks the “state of the art” of existing programs. The second paper introduces a new simulation program, which tries to overcome existing barriers. Specifically it explicitly recognizes the dynamic interaction between fuel cell system, drive train and optional additional energy storage.

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“…The model includes start up characteristics and emissions although it is not clear how detailed the model is 5 .…”

Section: Original Research Papermentioning

confidence: 99%

Fuel Cell Vehicle Simulation – Part 1: Benchmarking Available Fuel Cell Vehicle Simulation Tools

Hauer¹,

Moore

2003

Fuel Cells

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“…Simulink has rapidly been used in various research fields and likewise in the study of power systems [17,18]. In this study, we will take a multimachine power system example so as to illustrate the features and extent of a Simulink-based model for transient stability analysis.…”

Section: Introductionmentioning

confidence: 99%

Modeling, simulation, and optimal design of power system stabilizers using ABC algorithm

Ekinci¹,

Demirören²

2016

Turk J Elec Eng & Comp Sci

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This paper introduces a methodological system for modeling, simulation, and optimal tuning of the parameters of power system stabilizer (PSS) controllers in a multimachine power system so as to enhance transient stability. The model of a multimachine power system with PSS controllers is developed in MATLAB/Simulink for the simulation design.Simulink is a software instrument related to MATLAB, which is employed for modeling, simulating, and analyzing dynamical systems. The PSS controllers' design problem is expressed as an optimization problem; and the artificial bee colony (ABC) algorithm is utilized so as to examine the optimal PSS controller's parameters. The power system's transient stability performance is enhanced through diminishing a time domain-based objective function, where the oscillatory rotor speed deviation of the generator is obtained. The results of the nonlinear simulations substantiate the efficacy of the proposed modeling and tuning approach for power system stability enhancement. These outcomes likewise indicate that the proposed PSS controllers are operative in damping low frequency oscillations. In addition, comparing the ABC algorithm with the genetic algorithm method shows that better performance is achieved.

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“…With advances in switch technology that have made them suitable for the voltage and power levels necessary for power applications, power electronic switches can be used to build devices that could sustain repeated operations with high reliability and without wearing out [17]. There are 2 main types of solid state current: resonance based devices and impedance switch-in limiters.…”

Section: B Solid State Limitersmentioning

confidence: 99%

Novel Dual-FCL Connection with Neuro-fuzzy controller for Adding DG to a Power Distribution Utility

Vasudevarao¹,

Katuri²

2014

IOSRJEEE

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A power system simulation tool based on Simulink

Cited by 83 publications

References 3 publications

Fuel Cell Vehicle Simulation – Part 1: Benchmarking Available Fuel Cell Vehicle Simulation Tools

Fuel Cell Vehicle Simulation – Part 1: Benchmarking Available Fuel Cell Vehicle Simulation Tools

Modeling, simulation, and optimal design of power system stabilizers using ABC algorithm

Novel Dual-FCL Connection with Neuro-fuzzy controller for Adding DG to a Power Distribution Utility

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