Sliding mode based load-frequency control in power systems

Vrdoljak, Krešimir; Perić, Nedjeljko; Petrović, Ivan

doi:10.1016/j.epsr.2009.10.026

Cited by 212 publications

(123 citation statements)

References 28 publications

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“…As the general analytical solution has not been found [20], it was concluded that stability can be guaranteed if the control signal sampling time is different from the sampling time of the measured output samples. Such a control concept is called multirate output feedback [21][22][23]. The fast output sampling (FOS) method is based on sampling the output signal with higher frequency than the frequency of the control signal samples.…”

Section: Fast Output Sampling Algorithmmentioning

confidence: 99%

“…By setting two sampling times in the integer ratio (τ /T = N , N ∈ N), under the condition that N is greater or equal to the system observability index ν 0 , it is possible to make the estimation of state variables using the fast output sampling method [21,22,27]. Definition 1.…”

Section: Fast Output Sampling Algorithmmentioning

confidence: 99%

“…Definition 1. The observability index of the linear discrete system described by matrices A d , b d and c T is the smallest positive whole number ν 0 , which satisfies the following equation [21,22,27]:…”

Section: Fast Output Sampling Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

State Variables Estimation of Fuel Cell—Boost Converter System Using Fast Output Sampling Method

2013

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Original scientific paperEstimation of state variables of a peak current mode (PCM) controlled DC-DC boost converter supplied by a PEM fuel cell is described in this paper. Since this system is highly nonlinear and non-minimum phase, its state variables are estimated by using fast output sampling method. Estimated state variables are the converter output voltage and its first derivative, and they are suitable for model reference adaptive control or sliding mode based control techniques. The estimator has been designed in a way that it gives a good estimate of the state variables in the continuous and in the discontinuous conduction mode of the converter, and in the presence of measurement and process noise caused by converter switching-mode operation. Experimental results of estimating the state variables on a 450 W boost converter supplied by the emulator of the PEM fuel cell BCS 64-32 show good results of the estimation, regardless of the conduction mode of the converter, i.e. the operating point determined by its output current.Key words: state-space variables, estimation, fast output sampling, peak current mode control, boost converter, step-up converter, PEM fuel cell Procjena varijabli stanja sustava s gorivnimčlankom i uzlaznim pretvaračem metodom brzog uzorkovanja signala. U ovom radu obradena je procjena varijabli stanja sustava s istomjernim uzlaznim pretvaračem u vršnom strujnom načinu upravljanja napajanim PEM gorivnimčlankom. Budući da je taj sustav izrazito nelinearan te neminimalno-fazan, za procjenu njegovih varijabli stanja upotrebljena je metoda brzog uzorkovanja izlaznog signala. Procjenjene varijable stanja su izlazni napon uzlaznog pretvarača te njegova prva derivacija, te su pogodne za adaptivno upravljanje s referentnim modelom i upravljanje temeljeno na kliznim režimima. Procjenitelj je projektiran na način da daje dobru procjenu varijabli stanja u kontinuiranom i diskontinuiranom režimu rada pretvarača, te u uvjetima mjernog i procesnog šuma uzrokovanog sklopnim načinom rada pretvarača. Eksperimentalni rezultati procjene varijabli stanja na uzlaznom pretvaraču snage 450 W napajanim emulatorom gorivnogčlanka BCS 64-32 pokazuju dobre rezultate procjene, neovisno o režimu rada pretvarača, odnosno radnoj točki odredenoj njegovom izlaznom strujom.Ključne riječi: varijable stanja, procjena, brzo uzorkovanje signala, vršno strujno upravljanje, istosmjerni uzlazni pretvarač, PEM gorivničlanak

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Section: Fast Output Sampling Algorithmmentioning

confidence: 99%

Section: Fast Output Sampling Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

State Variables Estimation of Fuel Cell—Boost Converter System Using Fast Output Sampling Method

2013

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“…A normal sliding mode control cannot effectively handle mismatched uncertainty. Sliding mode control is used for frequency control of thermal and hydro power plants [12]. The effect of parameter variations and the effect of renewables are not discussed.…”

Section: Introductionmentioning

confidence: 99%

Observer based sliding mode frequency control for multi-machine power systems with high renewable energy

Tummala¹,

Inapakurthi²,

Ramanarao³

2018

J. Mod. Power Syst. Clean Energy

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With the global consciousness of climate change, renewable energy systems are prioritized over the conventional energy systems. The deep injection of renewables into the power systems is creating several challenges to the grid due to wide variations in their output power depending on the time of the day, weather etc. Of these challenges, frequency change plays a vital role in maintaining the power quality. This paper presents a novel sliding mode controller with non-linear disturbance observer to effectively mitigate the wide changes in the frequency. A sliding mode surface based on estimated disturbance along with states is designed. A sliding mode control law is proposed to compensate disturbances including variations in renewables, load and parameters under mismatched uncertainties. The proposed observer based controller is tested for three area multi-machine power system in MATLAB/Simulink. The simulated results proved to alleviate the frequency variations effectively compared to the conventional controllers.

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“…During the past decades, several control approaches have been proposed and applied to the LFC design problem, including optimal control, adaptive control, model predictive control, sliding mode control, and robust control, which can be found in [2][3][4][5][6], respectively. Each of these techniques has its own advantages and disadvantages.…”

Section: Introductionmentioning

confidence: 99%

Optimal fuzzy load frequency controller with simultaneous auto-tuned membership functions and fuzzy control rules

Zamani

Bijami²,

Sheikholeslam³

2014

Turk J Elec Eng & Comp Sci

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Abstract:In this paper, an auto-tuned fuzzy load frequency controller (FLFC)-based artificial bee colony (ABC) algorithm is developed to quench the deviations in the frequency and tie-line power due to load disturbances in an interconnected power system. Optimal tuning of membership functions (MFs) and fuzzy control rules is very important to improve the design performance and achieve a satisfactory level of robustness for a particular operation. In this work, to reduce the fuzzy system design effort and take large parametric uncertainties into account, a new systematic and simultaneous tuning method is developed for designing MFs and fuzzy rules. For this, the designing problem is restructured as an optimization problem and the ABC algorithm is employed to solve it. This newly developed method provides some advantages such as a flexible controller with a simple structure and easy algorithm. For the purpose of the proposed method's evaluation, the designed controller is applied to a 2-area power system with considerations regarding governor saturation and the results are compared to the one obtained by a classic proportional-integral controller.Simulation results show better operation and improved system parameters, such as the settling time and step response rise time, using the proposed approach, in the presence of system parameter variations.

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Sliding mode based load-frequency control in power systems

Cited by 212 publications

References 28 publications

State Variables Estimation of Fuel Cell—Boost Converter System Using Fast Output Sampling Method

State Variables Estimation of Fuel Cell—Boost Converter System Using Fast Output Sampling Method

Observer based sliding mode frequency control for multi-machine power systems with high renewable energy

Optimal fuzzy load frequency controller with simultaneous auto-tuned membership functions and fuzzy control rules

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