8,276 research outputs found

    Battery sizing for a stand alone passive wind system using statistical techniques

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    In this paper, an original optimization method to jointly determine a reduced study term and an optimum battery sizing is investigated. This storage device is used to connect a passive wind turbine system with a stand alone network. A Weibull probability density function is used to generate different wind speed data. The passive wind system is composed of a wind turbine, a permanent magnet synchronous generator feeding a diode rectifier associated with a very low voltage DC battery bus. This study is essentially based on a similitude model applied on an 8 kW wind turbine system. Our reference model is taken from a 1.7 kW optimized system. The wind system generated power and the load demand are coupled through a battery sized using a statistical approach

    Back-to-back Converter Control of Grid-connected Wind Turbine to Mitigate Voltage Drop Caused by Faults

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    Power electronic converters enable wind turbines, operating at variable speed, to generate electricity more efficiently. Among variable speed operating turbine generators, permanent magnetic synchronous generator (PMSG) has got more attentions due to low cost and maintenance requirements. In addition, the converter in a wind turbine with PMSG decouples the turbine from the power grid, which favors them for grid codes. In this paper, the performance of back-to-back (B2B) converter control of a wind turbine system with PMSG is investigated on a faulty grid. The switching strategy of the grid side converter is designed to improve voltage drop caused by the fault in the grid while the maximum available active power of wind turbine system is injected to the grid and the DC link voltage in the converter is regulated. The methodology of the converter control is elaborated in details and its performance on a sample faulty grid is assessed through simulation

    Integrated Optimal Design of a Passive Wind Turbine System: An Experimental Validation

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    This work presents design and experimentation of a full passive wind turbine system without active electronic part(power and control). The efficiency of such device can be obtained only if the system design parameters are mutually adapted through an Integrated Optimal Design (IOD) method. This approach based on multiobjective optimization, aims at concurrently optimizing the wind power extraction and the global system losses for a given wind speed profile while reducing the weight of the wind turbine generator. It allows us to obtain the main characteristics (geometric and energetic features) of the optimal Permanent Magnet Synchronous Generator (PMSG) for the passive wind turbine. Finally, experiments on the PMSG prototype built from this work show a good agreement with theoretical predictions. This validates the design approach and confirms the effectiveness of such passive device

    Model simplification and optimization of a passive wind turbine generator

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    In this paper, the design of a "low cost full passive structure" of wind turbine system without active electronic part (power and control) is investigated. The efficiency of such device can be obtained only if the design parameters are mutually adapted through an optimization design approach. For this purpose, sizing and simulating models are developed to characterize the behavior and the efficiency of the wind turbine system. A model simplification approach is presented, allowing the reduction of computational times and the investigation of multiple Pareto-optimal solutions with a multiobjective genetic algorithm. Results show that the optimized wind turbine configurations are capable of matching very closely the behavior of active wind turbine systems which operate at optimal wind powers by using a MPPT control device

    Robust design of a passive wind turbine system

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    The effectiveness of full passive Wind Turbine (WT) systems has been recently demonstrated. Such low cost and reliable structures without active control and with a minimum number of sensors can be efficient only if the system design parameters are mutually adapted through an integrated optimal design approach. Even if there is a good agreement between theoretical design models and an experimental prototype, it is relevant to evaluate the WT efficiency with respect to design variable variations. Thus, this work is devoted more specifically to the sensitivity analysis of a passive WT system according to electrical variable variations of the Permanent Magnet Synchronous Generator (PMSG). It also investigates the interest of a robust design approach for reducing the sensitivity of the WT efficiency to specific variable variations

    A Downsizing Strategy for Combinatorial PMSG Based Wind Turbine and Micro-SMES System Applied in Standalone DC Microgrid

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    This paper presents a combinatorial standalone permanent magnet synchronous generator (PMSG) based variable speed wind turbine (VSWT) and small-size superconducting magnetic energy storage (SMES) system into the DC microgrid system. The principal purpose of SMES system is to preserve power balance by absorbing power during peak wind generation and to release it during low power generation. This work accomplished by describing the optimized design of the SMES solenoid coil, ensuring the desired energy storage capacity based on the simulated annealing (SA) algorithm. More importantly, the new control technique is developed for bi-directional DC-DC converter to level output power of the wind turbine depending on the demand thereby reducing the capacity of the DC-DC converter system. Detailed simulation studies implemented in PSCAD/EMTDC corroborate the superior robustness and balancing performance of the proposed micro-SMES controller with an optimal coil size under various situations including variable wind speed. This combination will result in “scaling-factors” knowledge through downsizing strategy which will lead to the most efficient system from cost cutting, energy savings, and downsizing viewpoints

    Affine projection algorithm based adaptive control scheme for operation of variable-speed wind generator

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    This study presents a novel adaptive control scheme for variable-speed wind turbine (VSWT) driven permanent magnet synchronous generator (PMSG) to ensure its operation under different operating conditions. The adaptive control scheme is based on the affine projection algorithm (APA) which provides a faster convergence and less computational complexity than the least-mean-square algorithm. The proposed adaptive controller is used to control both the generator-side converter and the grid-side inverter without giving additional tuning efforts. Each vector control scheme for the converter/inverter has four APA-based adaptive proportional-integral (PI) controllers. Detailed modelling and the control strategies of the system under study are demonstrated. Real wind speed data extracted from Hokkaido island, Japan is used in this study. The dynamic characteristics of a grid-connected VSWT-PMSG are investigated in details to ensure the proposed controller operation under different operating conditions. The effectiveness of the proposed adaptive controller is compared with that obtained using optimised PI controllers by Taguchi method. The validity of the adaptive vector control scheme is verified by the simulation results which are performed using PSCAD/EMTDC environment

    Frequency Control of Microgrid Network using Intelligent Techniques – ANN, PSO and ANFIS

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    The electric grid is a complex system that transmits electricity from the point of generation to the point of consumption. According to the IEA, worldwide energy-related carbon emissions in 2021 will be 36.3Gt, 60% greater than at the start of the industrial revolution. Researchers have used intelligent solutions for power system frequency regulation to ensure that the system\u27s frequency is maintained. A proper frequency control of the microgrid necessitates the modeling and study of the systems. To emulate the operation of the human brain, frequency control employs a variety of artificial intelligence-based computer algorithms. This thesis generates a complete state space model of a microgrid composed of solar power plants, wind turbines, battery storage systems, and backup generators. The system frequency control was created for this system and analyzed against a benchmark PID controller utilizing several intelligent controllers such as PSO optimized PID, ANN, and ANFIS. The suggested intelligent frequency controllers were be simulated and validated using MATLAB/ Simulink
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