scholarly journals Wind Turbine Generator Efficiency Based on Powertrain Combination and Annual Power Generation Prediction

2018 ◽  
Vol 8 (6) ◽  
pp. 858
Author(s):  
Dongmyung Kim ◽  
Byeongcheol Park ◽  
Joosup Jang
Keyword(s):  
Power Generation ◽  
Wind Turbine ◽  
Turbine Generator ◽  
Wind Turbine Generator

scholarly journals A Reliability Based Model for Wind Turbine Selection

2013 ◽  
Vol 2 (2) ◽  
pp. 69-74 ◽  
Author(s):  
A.K. Rajeevan ◽  
P.V. Shouri ◽  
Usha Nair
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Point Of View ◽  
Cube Root ◽  
Mathematical Relationship ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
A Site

A wind turbine generator output at a specific site depends on many factors, particularly cut- in, rated and cut-out wind speed parameters. Hence power output varies from turbine to turbine. The objective of this paper is to develop a mathematical relationship between reliability and wind power generation. The analytical computation of monthly wind power is obtained from weibull statistical model using cubic mean cube root of wind speed. Reliability calculation is based on failure probability analysis. There are many different types of wind turbinescommercially available in the market. From reliability point of view, to get optimum reliability in power generation, it is desirable to select a wind turbine generator which is best suited for a site. The mathematical relationship developed in this paper can be used for site-matching turbine selection in reliability point of view.

Almighty High Output Type Intelligent Wind Turbine Generator With Tandem Rotors

2007 ◽  
Author(s):  
Toshiaki Kanemoto ◽  
Hiromi Mitarai ◽  
Koichi Kubo ◽  
Noboru Aoki ◽  
Nobuyuki Esaki ◽  
...  
Keyword(s):  
Power Generation ◽  
Wind Turbine ◽  
Electric Power ◽  
Axial Distance ◽  
Control Mechanisms ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
Weak Points ◽  
Rotor Profiles ◽  
High Output

Wind is clean, renewable, and homegrown energy source of electric power generation, and has been positively/effectively utilized to cope with the warming global environment. The conventional turbines with large-sized wind rotor generate high output at moderate wind. The power generation of the small-sized wind rotor is low but is suitable for weak wind. That is, the size of the wind rotor must be correctly/appropriately selected in conformity with the wind circumstances. Moreover, the turbines must be equipped with the brake and/or the pitch control mechanisms, in general, to suppress the abnormal rotation and the generated overload at the stronger wind, and to keep good quality of the electric power. To overcome above weak points, the authors have invented the superior wind turbine generator, as shown in Fig. 1. This unit was called “Intelligent Wind Turbine Generator” by the authors, as the rotational speeds of the tandem wind rotors are adjusted pretty well in cooperation with the two armatures of the generator in response to the wind speed. This unit is composed of the large–sized wind rotor, the small-sized wind rotor and the peculiar generator with the inner and the outer armatures without the conventional stator. The front and the rear wind rotors drive the inner and the outer armatures respectively as shown in Fig.1. The rotational torque is counter balanced between the inner and the outer armatures of the generator. The rotational direction and the speed of both wind rotors/armatures are free, and automatically determined in response to the wind circumstance. The superior power generation of the proposed wind turbine generator was verified in the previous report. Continuously, this paper shows the effects of the front wind rotor profiles, the axial distance and the diameter ratio between both wind rotors on the turbine characteristics, in accompanying with the flow conditions around the tandem wind rotors-were experimentally investigated and shows the characteristics of the superior generator.

scholarly journals A New Pitch Angle Control Method of Wind Turbine Generators Based on Feedforward Wind Speed Information

2019 ◽  
Vol 122 ◽  
pp. 04001
Author(s):  
Mouayad Sahib ◽  
Thaker Nayl
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Pitch Angle ◽  
Control Method ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
Intelligent Control System ◽  
Turbine Generators ◽  
New Strategy

In this work, a new strategy to control the pitch angle of wind turbine generator is proposed. The strategy is based on designing an intelligent control system capable of maintaining a stable minimum fluctuating power generation. This can be achieved by providing the wind speed information to the controller in advance and hence allowing the controller to take the optimum action in controlling the blade pitch angle. A model based optimizer uses Model Predictive Control (MPC) technique to predict the wind turbine generator future behaviour and select the optimal control actions assisted by the wind speed information while satisfying the power generation constraints. The simulation results show that a significant improvement can be made using the proposed control method.

wLEACH: Real-time Meteorological Data based Wind LEACH

2020 ◽  
Vol 10 ◽  
Author(s):  
Chaudhari Monali ◽  
Bhaskar A. A
Keyword(s):  
Power Generation ◽  
Wind Turbine ◽  
Real Time ◽  
Meteorological Data ◽  
Electrical Energy ◽  
Sensor Nodes ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
Mppt Controller ◽  
Hourly Basis

Introduction: Nowadays, Wireless Sensor Network (WSN) plays an important role in various fields. The limited power capability of the sensor nodes in the WSN brings constraints on the performance of the network. Low energy adaptive clustering hierarchy (LEACH) is a promising protocol for WSN that suffers from higher energy consumption. Objective: The primary objective of this study is to give an alternate harvesting resource power to sensor nodes in the LEACH algorithm which can be equally capable of providing the same or some time better results. Method: This study is based on real-time meteorological data. A real-time wind speed data is taken for the starting of a day to the end of the day on an hourly basis from the weather forecast. Now to convert this rotational energy into electrical energy, we used two types of wind turbines. For the proposed methodology, a micro wind turbine generator and 300watt wind turbine are used. Then this converted electrical energy is given to sensor nodes. For the clustering, the wind power operated nodes are given maximum preference to be elected as the cluster heads based on real-time wind meteorological data. We consider 10 wind-powered sensor nodes. As we increase the number of wind-powered sensor nodes in the network the performance is increased in terms of a lifetime but then increases the complexity of the network. Theses wind-powered nodes remain alive in the network. Since the deployment of the sensor nodes is random each simulation runs for 5 times and the average of first node dead, half node dead and last node dead is considered. Results: The experimental results for the micro wind turbine generator are compared based on with and without the MPPT controller. MPPT controller gives the maximum power by using the tip speed ratio control, power signal feedback control, and hill climb search control method. Therefore, the network lifetime should be higher for the MPPT based wind generator. Network lifetime and Energy consumption are compared for a micro wind turbine generator and 300watt wind turbine. Finally, the performance of the proposed system is compared with the modified solar LEACH implemented using real-time meteorological data. Conclusion: This paper has investigated the wind-based LEACH which uses the real-time meteorological data for the selection of the cluster head. Two types of wind generators are considered for the implementation and it is found that the performance of the commercial 300W wind turbine and the micro wind turbine with and without MPPT are almost similar since the data from both wind turbines are given on hourly basis. The performance of the wLEACH is compared with the sLEACH which shows that the network lifespan of the wLEACH is also nearly same compared to the sLEACH. But it is found that wind power generation is cheaper and efficient than solar power generation. So, this proposed wLEACH provides a cost-efficient solution.

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