Design and analysis of an axial magnetic flux wind generator

Claudiu, Brad; Vadan, Ioan; Berinde, Ioan

doi:10.1109/mps.2017.7974377

Cited by 6 publications

(2 citation statements)

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“…Se requieren imanes con un alto grado de magnetización, que hagan posible la ubicación de varios imanes en cada rotor [8,9]; además, la dirección de su polarización debe ser pertinente para esta aplicación; por lo que se seleccionaron imanes de neodimio grado 40 (N40)…”

Section: Imanes Permanentesunclassified

Caracterización de un generador de flujo axial para aplicaciones en energía eólica

Rosero

Claudio-Medina

Mayorga-Pardo

2018

ings

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Forma sugerida de citación: Carrillo, M.; Claudio, C.; Mayorga, A. (2018). «Caracterización de un generador de flujo axial para aplicaciones en energía eólica». Ingenius. N.• 19, (enero-junio Resumen AbstractEl aprovechamiento de los recursos energéticos no convencionales en los últimos años se ha desarrollado principalmente con la intención de disminuir el uso de combustibles. A mediana y pequeña escala la tendencia mundial, cuando se habla de generación eléctrica utilizando la energía eólica, es el uso de generadores de imanes permanentes. Los generadores de flujo axial son lo que se encuentran con mayor frecuencia a disposición. La principal característica de estos generadores es su capacidad de entregar energía eléctrica a bajas revoluciones, con una eficiencia aceptable. En este proyecto de investigación se caracterizaron dos tipos de generadores de flujo axial; uno con bobinas en serie y otro con bobinas en paralelo, con la intención de valorar el rendimiento de cada uno. El diseño parte de la determinación del flujo magnético, número de revoluciones, número de polos, número de bobinas, voltaje de salida y pérdidas eléctricas, para luego realizar el contraste a través de la toma de datos de amperaje y voltaje con respecto al cálculo teórico; la finalidad es establecer la eficiencia que presentan cada una de las configuraciones. Se estableció que el generador en serie posee características que lo convierten en una configuración que tiene una eficiencia mayor que la del generador en paralelo.The use of unconventional energy resources in recent years has developed mainly with the intention of reducing the use of fossil fuels to obtain electricity. When talking about electricity generation at medium and small scale, the global trend while taking advantage of wind energy, is the use of permanent magnet generators. Axial flow generators are the most often available: the main feature of these generators is their ability to deliver electrical power at low revolutions, with an acceptable efficiency. In this research project two types of axial flow generators were characterized; one with coils in series and another with coils in parallel, with the intention of evaluating the performance of each one. The design starts from the determination of the magnetic flux, number of revolutions, number of poles, number of coils, output voltage and electrical losses, to then carry out the contrast through the data acquisition of amperage and voltage with respect to the theoretical calculation; the purpose is to establish the efficiency of each of the configurations. It was established that the series generator has characteristics that make it a configuration that has an efficiency greater than that of the generator in parallel.

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Section: Imanes Permanentesunclassified

Caracterización de un generador de flujo axial para aplicaciones en energía eólica

Rosero

Claudio-Medina

Mayorga-Pardo

2018

ings

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“…The generation is dependent on the flow of air and the minimum amount of wind is required to run the system. Furthermore, a transformer is being used to step up the voltages which are sent to the grid [10]. In the plain areas such as in Punjab and Sindh, the flow of air is maximum in flat areas or in plain areas which is a positive point in the production of more amount of electrical power throughout mechanical input in a way so it can be rotated smoothly without any interruption.…”

Section: Introductionmentioning

confidence: 99%

Introducing AI applications in engineering education (PBL): An implementation of power generation at minimum wind velocity and turbine faults classification using AI

Khan,

Alam,

Rizvi

et al. 2023

Comp Applic In Engineering

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This article explores the integration of artificial intelligence (AI) applications into project‐based learning (PBL) education as a means to enhance students' education. Specifically, the implementation of AI in the context of power generation is addressed, focusing on achieving power generation at minimum wind velocity and classifying turbine faults using AI techniques. The researchers have proposed a novel generating unit which is going to generate 1 KW of electric power at a specific flow rate of air and the generated power will be stored in the battery bank through the charge controller and then the load is driven from the battery through an inverter. Iron or core losses (Hysteresis, Eddy Current losses) can be acknowledged as one of the major reasons for the inefficiency of conventional generators, therefore anovel coreless model generator was proposed which also improved efficiency and reduces drag. Wind Turbine prototype was fabricated and deployed for the testing and validation of the proposed novel design. The design produced outstanding power ratings and electrical generation characteristics compared with other existing strategies at minimal air flow. Results proved that the proposed coreless axial flux generator has the capability to produce a better power rating compared with the existing wind turbine generators. Proposed Axial flux achieved 10.73 watt power at wind velocity at around 80 rpm. At a wind velocity of 10 m/s and around 800 rpm 313–330 kwh was produced by the proposed generator while the conventional generator produced around 300 kwh. The proposed generator design performed 35% better in terms of production efficiency under load and no load conditions. Moreover, faults in turbines are very common due to the various temperatures, therefore the faults have been classified using state‐of‐the‐art AI‐based classifiers. A comparison of space vector modulation (SVM) and Naive Bayes classifiers was performed in the study to classify wind turbine faults. It was found that both classifiers performed well in achieving high accuracy. SVM achieved a slightly higher accuracy of 0.9861 compared with Naive Bayes, which achieved an accuracy of 0.967. Based on the results, it can be inferred that SVM may be a more suitable classifier for wind turbine fault classification. The case study results demonstrated the potential of AI applications in PBL education, offering students a multidisciplinary learning experience that enhances their technical knowledge, problem‐solving skills, and teamwork abilities.

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Suitable Electric Generator for Pico-Hydro Power Plant in Ambato–Huachi–Pelileo Water Irrigation Channel

Cumbajín

Sánchez

Hidalgo

et al. 2020

Advances in Intelligent Systems and Computing

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Design and analysis of an axial magnetic flux wind generator

Cited by 6 publications

References 0 publications

Caracterización de un generador de flujo axial para aplicaciones en energía eólica

Caracterización de un generador de flujo axial para aplicaciones en energía eólica

Introducing AI applications in engineering education (PBL): An implementation of power generation at minimum wind velocity and turbine faults classification using AI

Suitable Electric Generator for Pico-Hydro Power Plant in Ambato–Huachi–Pelileo Water Irrigation Channel

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