Optimal fuzzy logic controller design using particle swarm optimization for wind-natural gas power system

Chokpanyasuwan, C.; Pothiya, S.; Anantasate, S.; Bhasaputra, Pornrapeepat

doi:10.1109/ecticon.2009.5136987

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…To enhance the frequency stability in isolated power system, some research works have successfully proposed control design methods of the pitch controller in the wind side and the governor in the diesel side simultaneously, to damp the frequency fluctuation such as optimization of controller parameters using ISE technique (7) , fuzzy logic (8) etc. In (9) (10), the authors proposed new load frequency control method combining a PID controller and a disturbance observer for large penetration of wind power generations. This work can significantly improve the performance of the controllers and power system.…”

Section: Introductionmentioning

confidence: 99%

Robust PI-based Frequency Control of Isolated Wind-Diesel Power System with Coordinated Governor, Pitch and Battery Controller

2011

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A penetration of renewable energy sources such as photovoltaic, wind power etc to prevent global warming is become increasing highly. However, a random unpredictable wind power output may cause frequency fluctuation on isolated hybrid wind-diesel power system. This paper proposes design of coordinated control of governor, pitch and battery to stabilize frequency fluctuation in isolated wind-diesel power system. A well coordinated control between governor, pitch and battery controller are able to improve a performance and also minimize an interaction between the controllers. The structure of the proposed controllers are the first-order PI controller. They are simple and easy to implement in power system utilities. The robustness of the proposed PI controllers are guaranteed by applying an inverse additive perturbation to represent possible unstructured uncertainties in the power system such as variation of system parameters, generating and loading conditions etc. The proposed PI control parameters are optimized and achieved by a genetic algorithm (GA). Simulation studies have been done to show the control effect and robustness of the proposed PI controller in isolated hybrid wind-diesel power system against various disturbances and system uncertainties.

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Section: Introductionmentioning

confidence: 99%

Robust PI-based Frequency Control of Isolated Wind-Diesel Power System with Coordinated Governor, Pitch and Battery Controller

2011

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Particle swarm optimization based fuzzy logic controller for autonomous green power energy system with hydrogen storage

Safari

Ardehali

Sirizi

2013

Energy Conversion and Management

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ANFIS based Neuro-Fuzzy Controller in LFC of Wind-Micro Hydro-Diesel Hybrid Power System

Dhanalakshmi¹,

Palaniswami²

2012

IJCA

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This paper presents the design and analysis of Neuro-Fuzzy controller based on Adaptive Neuro-Fuzzy Inference System (ANFIS) architecture for Load frequency control of an isolated wind-micro hydro-diesel hybrid power system, to regulate the frequency deviation and power deviations. Due to the sudden load changes and intermittent wind power, large frequency fluctuation problem can occur. This newly developed control strategy combines the advantage of neural networks and fuzzy inference system and has simple structure that is easy to implement. So, in order to keep system performance near its optimum, it is desirable to track the operating conditions and use updated parameters to control the system. Simulations of the proposed ANFIS based Neuro-Fuzzy controller in an isolated wind-micro hydro-diesel hybrid power system with different load disturbances are performed. Also, a conventional proportional Integral (PI) controller and a fuzzy logic (FL) controller were designed separately to control the same hybrid power system for the performance comparison. The performance of the proposed controller is verified from simulations and comparisons. Simulation results show that the performance of the proposed ANFIS based Neuro-Fuzzy Controller damps out the frequency deviation and attains the steady state value with less settling time. The proposed ANFIS based Neuro-Fuzzy controller provides best control performance over a wide range of operating conditions.

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Optimal fuzzy logic controller design using particle swarm optimization for wind-natural gas power system

Cited by 3 publications

References 5 publications

Robust PI-based Frequency Control of Isolated Wind-Diesel Power System with Coordinated Governor, Pitch and Battery Controller

Robust PI-based Frequency Control of Isolated Wind-Diesel Power System with Coordinated Governor, Pitch and Battery Controller

Particle swarm optimization based fuzzy logic controller for autonomous green power energy system with hydrogen storage

ANFIS based Neuro-Fuzzy Controller in LFC of Wind-Micro Hydro-Diesel Hybrid Power System

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