Adaptive neuro-fuzzy inference system to improve the power quality of a split shaft microturbine power generation system

Oğuz, Yüksel; Üstün, Seydi Vakkas; Yabanova, İsmail; Yumurtacı, Mehmet; Guney, Irfan

doi:10.1016/j.jpowsour.2011.09.057

Cited by 24 publications

(14 citation statements)

References 41 publications

(27 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…An adaptive neural network has the advantages of learning ability, optimization and balancing. However, a fuzzy logic is a method based on rules constructed by the knowledge of experts [42]. The good performance and effectiveness of fuzzy logic have been approved in nonlinear and complicated systems.…”

Section: Adaptive Neuro-fuzzy Inference Systemsmentioning

confidence: 99%

Improvement of Microgrid Dynamic Performance under Fault Circumstances using ANFIS for Fast Varying Solar Radiation and Fuzzy Logic Controller for Wind System

Izadbakhsh¹,

Rezvani²,

Gandomkar³

2014

Archives of Electrical Engineering

View full text Add to dashboard Cite

Abstract:The microgrid (MG) technology integrates distributed generations, energy storage elements and loads. In this paper, dynamic performance enhancement of an MG consisting of wind turbine was investigated using permanent magnet synchronous generation (PMSG), photovoltaic (PV), microturbine generation (MTG) systems and flywheel under different circumstances. In order to maximize the output of solar arrays, maximum power point tracking (MPPT) technique was used by an adaptive neuro-fuzzy inference system (ANFIS); also, control of turbine output power in high speed winds was achieved using pitch angle control technic by fuzzy logic. For tracking the maximum point, the proposed ANFIS was trained by the optimum values. The simulation results showed that the ANFIS controller of grid-connected mode could easily meet the load demand with less fluctuation around the maximum power point. Moreover, pitch angle controller, which was based on fuzzy logic with wind speed and active power as the inputs, could have faster responses, thereby leading to flatter power curves, enhancement of the dynamic performance of wind turbine and prevention of both frazzle and mechanical damages to PMSG. The thorough wind power generation system, PV system, MTG, flywheel and power electronic converter interface were proposed by using Mat-lab/Simulink.

show abstract

Section: Adaptive Neuro-fuzzy Inference Systemsmentioning

confidence: 99%

Improvement of Microgrid Dynamic Performance under Fault Circumstances using ANFIS for Fast Varying Solar Radiation and Fuzzy Logic Controller for Wind System

Izadbakhsh¹,

Rezvani²,

Gandomkar³

2014

Archives of Electrical Engineering

View full text Add to dashboard Cite

show abstract

“…Yuksel Oguz et al [27] have presented a design of adaptive neuro-fuzzy inference system (ANFIS) for the turbine speed control for purpose of improving the power quality of the power production system of a split shaft microturbine. To improve the operation performance of the microturbine power generation system (MTPGS) and to obtain the electrical output magnitudes in desired quality and value (terminal voltage, operation frequency, power drawn by consumer and production power), a controller depended on adaptive neuro-fuzzy inference system was designed.…”

Section: Related Recent Researches: a Brief Reviewmentioning

confidence: 99%

ABC and NFC based unified power quality conditioner for compensating power quality problem

Vardhan¹

2013

IOSR-JEEE

View full text Add to dashboard Cite

“…Moreover, FLC has already been integrated with other intelligent control theories to design adaptive interference models. For example, in [23], an adaptive neuro-fuzzy inference system was designed for controlling output voltage and frequency of a variable-speed wind power generation system. In general, regarding the above studies, their motivations originated from considering the nonlinear nature of WTs and uncertainties of models.…”

Section: Introductionmentioning

confidence: 99%

The integrated control of fuzzy logic and model-based approach for variable-speed wind turbine

Yang¹,

Song²,

Han³

et al. 2015

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

For a variable-speed wind turbine (VSWT), the primary objective of control is to maximize power generation while maintaining the desired rotor speed and avoiding equipment overloads. To fulfill the control objectives, the classical model-based control (MBC) has been widely used, which refers to two controllers: torque controller (TC) and pitch controller (PC). In this work, the drawbacks of MBC for VSWTs are studied extensively. It reveals that there are transition issues between the TC and PC, and over-speed problems under large turbulent wind when only MBC is taken.To improve the control performance of the VSWT, an integrated control solution is presented, in which three fuzzy logic control modules are designed to function in parallel with MBC modules. Potential integrated structures are also given and a structure suitable for industrial application is adopted in this study. The proposed solution is applied to update the raw control system of a 3.0 MW VSWT of the Chinese Ming Yang Wind Power, which is validated with nonlinear simulations by using the commercial wind turbine simulation tool Bladed in accordance with IEC standards. The results prove that good performance of the target wind turbine is guaranteed under the proposed integrated control structure.

show abstract

Adaptive neuro-fuzzy inference system to improve the power quality of a split shaft microturbine power generation system

Cited by 24 publications

References 41 publications

Improvement of Microgrid Dynamic Performance under Fault Circumstances using ANFIS for Fast Varying Solar Radiation and Fuzzy Logic Controller for Wind System

Improvement of Microgrid Dynamic Performance under Fault Circumstances using ANFIS for Fast Varying Solar Radiation and Fuzzy Logic Controller for Wind System

ABC and NFC based unified power quality conditioner for compensating power quality problem

The integrated control of fuzzy logic and model-based approach for variable-speed wind turbine

Contact Info

Product

Resources

About