A new fuzzy sliding mode controller for load frequency control of large hydropower plant using particle swarm optimization algorithm and Kalman estimator

Hooshmand, Rahmat‐Allah; Ataei, Mohammad; Zargari, Abolfazl

doi:10.1002/etep.609

Cited by 25 publications

(18 citation statements)

References 19 publications

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“…In this subsection, parameter of the ACE variable β is 0.2083 p.u.kW/Hz [25], synchronizing power coefficient of the tie line T s is 0.0866 s [25], gain of the additional state is picked up as 0.002. The sliding surface parameters of the SMC controller in (24) T according to Ackermann's formula. Other controller parameters in (24) are picked up as κ c = 0.1 and η c = 0.1.…”

Section: Grid-connected Modementioning

confidence: 99%

“…The sliding surface parameters of the SMC controller in (24) T according to Ackermann's formula. Other controller parameters in (24) are picked up as κ c = 0.1 and η c = 0.1. The load disturbance ∆P L is applied to the system at t = 0.…”

Section: Grid-connected Modementioning

confidence: 99%

“…In [20,21], two kinds of sliding-mode governors were investigated for hydropower plants. Other reports can be found in [22][23][24]. Usually, one assumption in most of the referred articles is that all the state variables of hydro power systems are measurable.…”

Section: Introductionmentioning

confidence: 99%

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Load Frequency Control for Micro Hydro Power Plants by Sliding Mode and Model Order Reduction

Qian

Liu

2015

Automatika

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Original scientific paperMicro hydro is treated as a major renewable energy resource. Such a kind of plants blooms because they can evade some dilemmas like population displacement and environmental problems. But their performance on the frequency index of power systems may be deteriorated in the presence of sudden small load perturbations and parameter uncertainties. To improve the performance, the problem of load frequency control (LFC) raises up. Design of state-based controllers on the aspect of modern control is challenging because only a part of the system states are measurable. This paper addresses the scheme of sliding mode control by model order reduction for the LFC problem of micro hydro power plants. The kind of plants usually has two operating modes, i.e., isolated mode and grid-connected mode. Under each operating mode, mathematical model and model reduction are investigated at first. According to the reduced-order model, a sliding mode control law is subsequently derived. Since the control law is applied to the original system, a sufficient condition about the system stability is proven in light of small gain theory. Simulation results illustrate the feasibility, validity and robustness of the presented scheme. Key words: Load Frequency Control, Micro Hydro Power Plants, Model Order Reduction, Sliding Mode ControlUpravljanje frekvencijom i radnom snagom mikro hidroelektrana kliznim režimom rada i redukcijom reda modela sustava. Mikro hidroelektrane smatraju se jednim od glavnih obnovljivih izvora energije. Ovakve elektrane su poglavito zanimljive pošto izbjegavaju dileme vezane za iseljavanje ljudi i utjecaj na okoliš. Međutim, njihov učinak na indeks frekvencije energetskih sustava može biti negativan zbog naglih manjih promijena u opterećenju i nesigurnosti parametara. Kako bi se unaprijedila učinkovitost, javlja se problem regulacije frekvencije i radne snage. Projektiranje regulatora po varijablama stanja sustava izazovan je problem, jer je mjerljiv samo dio stanja sustava. Ovajčlanak analizira problem upravljanja kliznim režimom rada reducirajući red modela sustava kod regulacije frekvencije i radne snage mikro hidroelektrana. Ovakve elektrane mogu raditi u samostalnom režimu rada ili biti spojene na distribucijsku mrežu. Za oba ražima rada prvo se istražuju matematički modeli te potom njihova redukcija. S obzirom na model reduciranog reda izvodi se upravljački zakon kliznog režima rada. Pošto se zakon upravljanja primjenjuje na izvorni sustav, dokazan je dovoljan uvjet za stabilnost u vidu teorije malog pojačanja. Simulacijski rezutati pokazuju izvedivost, ispravnost i robustnost predloženog pristupa.Ključne riječi: upravljanje frekvencijom i radnom snagom, mikro hidroelektrane, redukcija reda modela sustava, upravljanje u kliznog režimu rada

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Section: Grid-connected Modementioning

confidence: 99%

Section: Grid-connected Modementioning

confidence: 99%

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Load Frequency Control for Micro Hydro Power Plants by Sliding Mode and Model Order Reduction

Qian

Liu

2015

Automatika

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“…The first stage conducts the state trajectory to the sliding surface. The second stage is the converging of the system output to the desired output, based on the desired dynamics [30]. Therefore, as the sliding surface becomes stable (i.e.…”

Section: Smcmentioning

confidence: 99%

Control of SVC based on the sliding mode control method

Köse¹,

Kizmaz²,

Abacı³

et al. 2014

Turk J Elec Eng & Comp Sci

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Abstract:A genetic algorithm (GA)-based sliding mode controller is proposed to improve the voltage stability of a power system with a static var compensator. The proposed controller is examined for improving the load bus voltage, which changes under different demanding powers, and its performance for transient analysis is compared with the ZieglerNichols proportional-integral (ZNPI), Lyapunov-based sliding mode control (LASMC), and GA-based proportionalintegral-derivative (GAPID) controllers. The dynamic equations, consisting of a 2-bus nonlinear system, are converted to a mathematical description of sliding mode techniques. The optimum values of the sliding mode controller and proportional-integral-derivative (PID) coefficients that are required are calculated using the GA technique. Output voltage performances are obtained based on the demanding powers, which are at a constant variation. In this process, sliding mode, ZNPI, GAPID, and LASMC controllers are preferred in order to control the system. The results show that the GA sliding mode controller method is more effective than the ZNPI, GAPID, and LASMC controllers in voltage stability enhancement.

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“…These algorithms have become a popular choice for solving complex optimization problems because of their flexibility, generality, and ease of use. The GA and PSO techniques although are reported to minimize the chattering but they sometimes get trapped in the local minima . The other algorithms may also suffer from difficulties such as premature convergence and more computational time in case of the large dimension system .…”

Section: Introductionmentioning

confidence: 99%

Hybridized gravitational search algorithm tuned sliding mode controller design for load frequency control system with doubly fed induction generator wind turbine

Dahiya

Sharma

Naresh

2017

Optim Control Appl Methods

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Summary In this paper, the load frequency regulation problem of 2‐area interconnected power system is resolved using the sliding mode control (SMC) methodology. Interconnected 2‐area power systems with and without doubly fed induction generator wind turbines are considered for implementing the proposed optimal control methodology. Here, a heuristic gravitational search algorithm (GSA) and its variants such as opposition learning–based GSA (OGSA), disruption‐based GSA (DGSA), and disruption based oppositional GSA (DOGSA) are employed to optimize the switching vector and feedback gains of SMC. In order to overcome the inherent chattering problem in SMC, the control signals are considered in the objective function. The robustness of optimized SMC is analyzed by the inclusion of nonlinearities such as generation rate constraint (GRC), governor deadband, and time delay during the signal processing between the control areas, which are present in the real‐time power system. The insensitiveness of the optimal controller is shown by variation in system parameters like loading condition, speed governor constant, turbine constant, and tie‐line power coefficient. Further, the optimal SMC has been studied with significant load variations and wind power penetration levels in the control areas. The potential of proposed SMC design with chattering reduction feature is shown and validated by comparing the results obtained with the other reported methods in the literature.

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A new fuzzy sliding mode controller for load frequency control of large hydropower plant using particle swarm optimization algorithm and Kalman estimator

Cited by 25 publications

References 19 publications

Load Frequency Control for Micro Hydro Power Plants by Sliding Mode and Model Order Reduction

Load Frequency Control for Micro Hydro Power Plants by Sliding Mode and Model Order Reduction

Control of SVC based on the sliding mode control method

Hybridized gravitational search algorithm tuned sliding mode controller design for load frequency control system with doubly fed induction generator wind turbine

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