Analysis of a new horizontal axes wind turbine with 6/3 blades

Chetan, S.; Festila, C.; Dulf, Éva-Henrietta; Both-Rusu, Roxana

doi:10.1109/aqtr.2018.8402770

Cited by 9 publications

(2 citation statements)

References 5 publications

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“…Ahmed et al [11] used the Savonius model to create a compact vertical axis wind turbine that utilized a 50:1 ratio gearbox. Chetan et al [12] presented a wind turbine system that can be converted into a three-or six-blade wind turbine depending on the wind speed. The turbine has two identical systems, a star-connected three pins system with appropriate length, and a system of three springs connected sequentially between the pins and blades.…”

Section: Background Studymentioning

confidence: 99%

An intelligent wind turbine with yaw mechanism using machine learning to reduce high-cost sensors quantity

Bhandari Abhi,

Kumar Saha,

Tahmidul Kabir

et al. 2023

IJEECS

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In this paper, with the assistance of some tools and a machine learning model, a smart wind turbine was formed that eliminates some expensive sensors and reduces sensor complexity. Squirrel cage induction generator (SCIG) and six rotor blades make up the proposed design, and depending on the wind's direction, the turbine itself can rotate the rotor hub to produce energy more effectively. Additionally, two stepper motors are coupled to the yaw mechanism with the aid of the rotor hub, and the entire controlling procedure will depend on the direction of the wind. The rotor hub must continuously revolve in the same direction as the wind to maximize wind energy utilization. Additionally, to correctly predict wind degrees, a machine learning model was deployed. Random forest regression was used to train and predict the wind direction. The model is deployed in Raspberry Pi, where the incoming sensor values are being stored. Using the generated data, machine learning model was trained and it can be concluded that the model can potentially replace some of the expensive sensors to reduce cost. The model can be used for similar weather conditions only based on machine learning model and fewer sensors.

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Section: Background Studymentioning

confidence: 99%

An intelligent wind turbine with yaw mechanism using machine learning to reduce high-cost sensors quantity

Bhandari Abhi,

Kumar Saha,

Tahmidul Kabir

et al. 2023

IJEECS

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“…The surrounding conditions have an important factor for selection the type of wind turbine for power generation. Also, choice applicable turbine needs to take into account the blades number of turbine which is affected by the wind speed 8) . The turbine should not be rotate heavy due to wind; therefore, the aerodynamic characteristics should be considered during a turbine [9][10] .…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Wind Turbine Power Generation Utilizing Discharged Air of Air Conditioner Blower

Jessam¹

2022

Evergreen

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The world's energy demand has become unbridled in the past years. The increasing demand for conventional energy sources (fossil fuels, nuclear) became under tremendous pressure which is resulting from continuous use of it. This continuous use leads to a scarcity of fossil fuels. This has sparked widespread research in the field of unconventional energy sources such as hydro energy, wind energy and thermal energy. Wind can be used as a renewable energy to generate the electrical energy. In the current study, the wind of the air conditioning exhaust has been utilized as a renewable energy to generate the electrical energy. The wind speed is relatively stable every time, this feature encourages the use of air conditioning exhaust. Different wind speed for three types of air conditioning 1HP, 2HP and 3HP was investigated experimentally. The maximum wind speed with 3 HP was 7.1 m/s and 7.2 m/s with anemometer attached to the blower of air conditioner at distance 24 cm on the left and right of the middle of air conditioner blower, respectively. The wind turbine has the ability to convert the wind energy of blower into electrical energy. The wind turbine, Savonius type L, was connected together with direct current (DC) generator and alternating current (AC) generator and fixed inside the Perspex duct. The Perspex duct was connected to the air conditioning exhaust. It was obtained the AC generator can generate voltage 35 V, current 0.51 A and output power14.28 W with adopting 3 HP capacity air conditioner. While the DC generator can generate 46 V, current 0.32 A and output power 14.72 W with adopting 3 HP capacity air conditioner. The generated electrical energy can be used for operating small devices that is need low amount voltage or to turn on the LED lights.

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