Wind speed short term forecast by neuro fuzzy modeling with aid of Mutual Information at Manjil Wind Power Plant

Author(s):  
Omid Ghiasvand ◽  
Amir Ghiasvand
2017 ◽  
Vol 18 (2) ◽  
pp. 68
Author(s):  
Made Padmika ◽  
I Made Satriya Wibawa ◽  
Ni Luh Putu Trisnawati

A prototype of a wind power plant had been created using a ventilator  as a generator spiner. This power plant utilizes wind speed as its propulsion. Electricity generated in the DC voltage form between 0 volts up to 7.46 volts. The MT3608 module is used to stabilize and raise the voltage installed in the input and output of the charging circuit. For instrument testing, the wind speed on 0 m/s up to 6 m/s interval used. Maximum output of this tool with a wind speed of 6 m/s is 7.46 volts.


Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1587
Author(s):  
Krzysztof Wrobel ◽  
Krzysztof Tomczewski ◽  
Artur Sliwinski ◽  
Andrzej Tomczewski

This article presents a method to adjust the elements of a small wind power plant to the wind speed characterized by the highest annual level of energy. Tests were carried out on the basis of annual wind distributions at three locations. The standard range of wind speeds was reduced to that resulting from the annual wind speed distributions in these locations. The construction of the generators and the method of their excitation were adapted to the characteristics of the turbines. The results obtained for the designed power plants were compared with those obtained for a power plant with a commercial turbine adapted to a wind speed of 10 mps. The generator structure and control method were optimized using a genetic algorithm in the MATLAB program (Mathworks, Natick, MA, USA); magnetostatic calculations were carried out using the FEMM program; the simulations were conducted using a proprietary simulation program. The simulation results were verified by measurement for a switched reluctance machine of the same voltage, power, and design. Finally, the yields of the designed generators in various locations were determined.


KnE Energy ◽  
2015 ◽  
Vol 2 (2) ◽  
pp. 172
Author(s):  
Tedy Harsanto ◽  
Haryo Dwi Prananto ◽  
Esmar Budi ◽  
Hadi Nasbey

<p>A vertical axis wind turbine triple-stage savonius type has been created by using simple materials to generate electricity for the alternative wind power plant. The objective of this research is to design a simple wind turbine which can operate with low wind speed. The turbine was designed by making three savonius rotors and then varied the structure of angle on the three rotors, 0˚, 90˚ and 120˚. The dimension of the three rotors are created equal with each rotor diameter 35 cm and each rotor height 19 cm. The turbine was tested by using blower as the wind sources. Through the measurements obtained the comparisons of output power, rotation of turbine, and the level of efficiency generated by the three variations. The result showed that the turbine with angle of 120˚ operate most optimally because it is able to produce the highest output power and highest rotation of turbine which is 0.346 Watt and 222.7 RPM. </p><p><strong>Keywords</strong>: Output power; savonius turbine; triple-stage; the structure of angle</p>


Author(s):  
Sergey Sodnomovich Dorzhiev ◽  
Elena Gennadyevna Bazarova ◽  
Konstantin Sergeevich Morenko

This chapter describes the features of the work of wind-receiving devices in the insufficient power mode when the current wind speed is below the construction value of the wind power plant. The term “effective angle” is introduced. The importance of this problem is shown and the amount of time in the insufficient power mode, for example, wind power plant, is calculated. The main characteristics of an electrical generator and a wind receiving device are considered. The importance of the mapping the characteristics of the wind-receiving device and the electrical generator is shown.


Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 753 ◽  
Author(s):  
Jianfeng Dai ◽  
Yi Tang ◽  
Jun Yi

High-penetration wind power will count towards a significant portion of future power grid. This significant role requires wind turbine generators (WTGs) to contribute to voltage and reactive power support. The maximum reactive power capacity (MRPC) of a WTG depends on its current input wind speed, so that the reactive power regulating ability of the WTG itself and adjacent WTGs are not necessarily identical due to the variable wind speed and the wake effect. This paper proposes an adaptive gains control scheme (AGCS) for a permanent magnet synchronous generator (PMSG)-based wind power plant (WPP) to provide a voltage regulation service that can enhance the voltage-support capability under load disturbance and various wind conditions. The droop gains of the voltage controller for PMSGs are spatially and temporally dependent variables and adjusted adaptively depending on the MRPC which are a function of the current variable wind speed. Thus, WTGs with lower input wind speed can provide greater reactive power capability. The proposed AGCS is demonstrated by using a PSCAD/EMTDC simulator. It can be concluded that, compared with the conventional fixed-gains control scheme (FGCS), the proposed method can effectively improve the voltage-support capacity while ensuring stable operation of all PMSGs in WPP, especially under high wind speed conditions.


2014 ◽  
Vol 1008-1009 ◽  
pp. 137-143
Author(s):  
Ying Jie Qin ◽  
Shan Song ◽  
Bin Shi ◽  
Zhen Jian Xie ◽  
Li Wei Qiao

For power grid with large-scale wind energy, the short-term wind power prediction is important to the grid’s scheduling and stable operating. The overall short-term forecast for wind power connected to the grid relies on the wind velocity and historical power data. Firstly, K-means clustering is introduced to model the power grid, so that the relationship between wind velocity and power can be perfectly described. Considering that there are multiple factors contributing to the prediction of wind velocity and power, we use real data of 15 wind generating set to obtain dependable weight factors of all those dimensions. With the support of mass data, the prediction of power is proved by several measurements (ME, MRE, MAE, RMSE) to be accurate.


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