Power management of a variable speed wind turbine for stand-alone system using fuzzy logic

Minh, Huynh Quang; Nollet, Frederic; Essounbouli, Najib; Hamzaoui, Abdelaziz

doi:10.1109/fuzzy.2011.6007718

Cited by 13 publications

(8 citation statements)

References 24 publications

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“…Though, by analysing the alteration principle of the wind power, it is found that combined pitch and power management controller can regulate the produced wind power by regulating the angular rotational speed of the WT to optimum value. [14][15][16][17][18][19][20] The equilibrium between the power production and power consumption of the load is achieved when the total power generated by WPGS is equal to the total load demand in addition to the power losses. The prediction of the wind speed all around year in particular site area could be easier to estimate the obtainable wind power from the wind farm and that could satisfy the load power constraints.…”

Section: Power Management Using the Proposed Strategymentioning

confidence: 99%

“…The action of adjusting the turbine blades sequentially increases or decreases the power production. In the study of Minh et al, 18 a power management system has been developed and the power management communicates with innovatory pitch system to respond to changing load demands. 19 The power management is best employed with variable pitch control or stall control.…”

Section: Introductionmentioning

confidence: 99%

“…This model is preferred since it is cheaper to develop, covers a wider range of operating conditions and are more readily customizable in natural language terms. 18 Hence, as FLC has a higher advantage in dealing with the non-linear function, it is chosen as the control strategy to control the pitch actuator. This work mainly focuses on the power management of the wind farm composed of three variable speed WTs.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automated power management strategy for wind power generation system using pitch angle controller

Sitharthan¹,

Sundarabalan

Devabalaji

et al. 2019

Measurement and Control

142

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In this literature, a new automated control strategy has been developed to manage the power supply from the wind power generation system to the load. The main objective of this research work is to develop a fuzzy logic-based pitch angle control and to develop a static transfer switch to make power balance between the wind power generation system and the loads. The power management control system is a progression of logic expressions, designed based on generating power and load power requirement. The outcome of this work targets at an improved power production, active and reactive power compensation and ensures system load constraints. To validate the proposed control strategy, a detailed simulation study is carried out on a 9-MW wind farm simulation simulated in MATLAB/Simulink environment.

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Section: Power Management Using the Proposed Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Automated power management strategy for wind power generation system using pitch angle controller

Sitharthan¹,

Sundarabalan

Devabalaji

et al. 2019

Measurement and Control

142

View full text Add to dashboard Cite

show abstract

“…With the capability to track complex nonlinearity systems, artificial intelligence techniques have received considerable attention in the wind energy field. An artificial intelligence technique is a generalized term that encompasses artificial neural networks (ANNs) [10,11], fuzzy logic methods [12,13], and support vector machines (SVM) [6,[14][15][16][17][18][19][20][21]. Mohandes et al [16] used the SVM model to forecast the mean daily wind speed and compared the results with the multilayer perceptron (MLP) neural networks.…”

Section: Introductionmentioning

confidence: 99%

Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm

Wang

Zhou

Jiang

et al. 2015

Mathematical Problems in Engineering

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This paper develops an effectively intelligent model to forecast short-term wind speed series. A hybrid forecasting technique is proposed based on recurrence plot (RP) and optimized support vector regression (SVR). Wind caused by the interaction of meteorological systems makes itself extremely unsteady and difficult to forecast. To understand the wind system, the wind speed series is analyzed using RP. Then, the SVR model is employed to forecast wind speed, in which the input variables are selected by RP, and two crucial parameters, including the penalties factor and gamma of the kernel function RBF, are optimized by various optimization algorithms. Those optimized algorithms are genetic algorithm (GA), particle swarm optimization algorithm (PSO), and cuckoo optimization algorithm (COA). Finally, the optimized SVR models, including COA-SVR, PSO-SVR, and GA-SVR, are evaluated based on some criteria and a hypothesis test. The experimental results show that (1) analysis of RP reveals that wind speed has short-term predictability on a short-term time scale, (2) the performance of the COA-SVR model is superior to that of the PSO-SVR and GA-SVR methods, especially for the jumping samplings, and (3) the COA-SVR method is statistically robust in multi-step-ahead prediction and can be applied to practical wind farm applications.

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“…A power management system can control the power generation at optimum levels to meet the load power demand [10]. It can provide adequate energy based on the load demand and the availability of energy from the wind turbine.…”

Section: Introductionmentioning

confidence: 99%

Power Management System for Load Banks Supplied by Pitch Controlled Wind Turbine System

et al. 2012

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An automatic power management system, to monitor the distribution of power to a set of load banks, is presented in this paper. The required power is generated from a laboratory-size pitch-controlled wind turbine experimental workstation. The management system is a sequence of logic expressions, based on the generated power, a profile of the banks' states provided by the supervisor and the banks' priorities, to obtain an optimal behavior of the system and to ensure the load requirement. A modified PI pitch angle control is proposed to regulate the generated power for tracking the power reference in order to maintain a consistent brilliance of the load's LEDs, to reduce the activity of the pitch actuator and to deal with fluctuation problems. Experimental results are provided to show the effectiveness of the proposed automatic power management system for load banks supplied by a pitch controlled wind turbine.

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Power management of a variable speed wind turbine for stand-alone system using fuzzy logic

Cited by 13 publications

References 24 publications

Automated power management strategy for wind power generation system using pitch angle controller

Automated power management strategy for wind power generation system using pitch angle controller

Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm

Power Management System for Load Banks Supplied by Pitch Controlled Wind Turbine System

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