Dynamic vibrations in wind energy systems: Application to vertical axis wind turbine

Mabrouk, Imen Bel; Hami, Abdelkhalak El; Walha, Lassâad; Zghal, Bacem; Haddar, Mohamed

doi:10.1016/j.ymssp.2016.08.034

Cited by 43 publications

(11 citation statements)

References 15 publications

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“…Lift-type VAWTs, such as the Darrieus rotor with egg-beater blades (Φ-type) and the Darrieus rotor with straight blades (H-type), are the most widely used VAWTs [3,4]. Furthermore, their designs were improved with computer fluid dynamics (CFD) and finite element analysis (FEA), making them more efficient in energy conversion [5][6][7]. However, studies on VAWTs are limited when compared to those on horizontal wind turbines.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Study of a Rooftop Vertical Axis Wind Turbine Tower Based on an Automated Vibration Data Processing Algorithm

et al. 2018

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When constructed on tall building rooftops, the vertical axis wind turbine (VAWT) has the potential of power generation in highly urbanized areas. In this paper, the ambient dynamic responses of a rooftop VAWT were investigated. The dynamic analysis was based on ambient measurements of the structural vibration of the VAWT (including the supporting structure), which resides on the top of a 24-story building. To help process the ambient vibration data, an automated algorithm based on stochastic subspace identification (SSI) with a fast clustering procedure was developed. The algorithm was applied to the vibration data for mode identification, and the results indicate interesting modal responses that may be affected by the building vibration, which have significant implications for the condition monitoring strategy for the VAWT. The environmental effects on the ambient vibration data were also investigated. It was found that the blade rotation speed contributes the most to the vibration responses.

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Section: Introductionmentioning

confidence: 99%

Dynamic Study of a Rooftop Vertical Axis Wind Turbine Tower Based on an Automated Vibration Data Processing Algorithm

et al. 2018

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“…The number of hidden layer is estimated in the range from five to twenty according to some empirical methods [87][88][89][90][91][92][93][94][95][96][97][98][99]. To select the best one in this range, an experiment is done based on the 1st-360th series of the original wind speed series.…”

Section: Number Of Network Neuronsmentioning

confidence: 99%

Research and Application of Hybrid Forecasting Model Based on an Optimal Feature Selection System—A Case Study on Electrical Load Forecasting

Dong

Wang

et al. 2017

Energies

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Abstract:The process of modernizing smart grid prominently increases the complexity and uncertainty in scheduling and operation of power systems, and, in order to develop a more reliable, flexible, efficient and resilient grid, electrical load forecasting is not only an important key but is still a difficult and challenging task as well. In this paper, a short-term electrical load forecasting model, with a unit for feature learning named Pyramid System and recurrent neural networks, has been developed and it can effectively promote the stability and security of the power grid. Nine types of methods for feature learning are compared in this work to select the best one for learning target, and two criteria have been employed to evaluate the accuracy of the prediction intervals. Furthermore, an electrical load forecasting method based on recurrent neural networks has been formed to achieve the relational diagram of historical data, and, to be specific, the proposed techniques are applied to electrical load forecasting using the data collected from New South Wales, Australia. The simulation results show that the proposed hybrid models can not only satisfactorily approximate the actual value but they are also able to be effective tools in the planning of smart grids.

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“…It is clean and renewable; the application of wind energy is increased massively in the last few decades. Wind energy is one of the promising renewable energy resources [3]. Wind energy has utilized thought of Horizontal Axis Wind Turbine (HAWT) and Vertical Axis Wind Turbine (VAWT).…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Vertical Axis Wind Turbine Performance under Vibration

Sarkar

Julai

Nahar

et al. 2021

IJRCS

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An experimental study was conducted to study the effects of flow uniformity on vibration and power generation of a small vertical axis wind turbine (VAWT). Previous studies have confirmed that one of the sources of vibration in the turbine is due to aerodynamic forces, which are due to incident wind. Firstly, understanding vibration is essential before proceeding to the measurements. In this experiment, further understand the vibrations of the turbine in operation, the operating deflection shape (ODS) technique was used. A wind tunnel and flow conditioner were fabricated. Experimental modal analysis (EMA) was conducted, and the dynamic characteristics are gathered. The ODS was conducted for operating the turbine at different speeds, with and without the flow conditioner. Results from EMA and ODS are correlated to explain the behavior of structures. In conclusion, the flow conditioner tested did have a big impact on the response of the structure in terms of vibration up to 30% indifference, but not so much in power generated about 2% indifference.

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Dynamic vibrations in wind energy systems: Application to vertical axis wind turbine

Cited by 43 publications

References 15 publications

Dynamic Study of a Rooftop Vertical Axis Wind Turbine Tower Based on an Automated Vibration Data Processing Algorithm

Dynamic Study of a Rooftop Vertical Axis Wind Turbine Tower Based on an Automated Vibration Data Processing Algorithm

Research and Application of Hybrid Forecasting Model Based on an Optimal Feature Selection System—A Case Study on Electrical Load Forecasting

Experimental Study of Vertical Axis Wind Turbine Performance under Vibration

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