Evaluation of factors affecting wind turbine output power

El-Ahmar, M. H.; El‐Sayed, Abou‐Hashema M.; Hemeida, Ashraf Mohamed

doi:10.1109/mepcon.2017.8301377

Cited by 17 publications

(12 citation statements)

References 12 publications

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“…The turbine is also shut down and kept in parking mode when wind speed is above the cut-out value or during emergency conditions due to security. For wind-speed values between the cut-in and rated, the power P curve maintains a cubic relationship with respect to wind speed [16]. Figure 14 presents a power curve of a Vestas V164-8.0 turbine.…”

Section: Wind Turbinesmentioning

confidence: 99%

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How to Improve an Offshore Wind Station

Torres

Jesus²,

Lameirinhas

2022

Energies

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The ocean is approximately 71% of the Earth’s surface and has a lot of resources available. Nowadays, human beings are looking for renewable ways to obtain energy. Offshore power can be obtained in several different ways. Offshore wind power is the most used renewable offshore energy. Since 2017, offshore wind power has a competitive price in comparison with conventional sources. In the 2010s, offshore wind power grew at over 30% per year. Although it has remained less than one percent of the overall world electricity generation, offshore wind power becomes quite relevant on the northern European countries from 2020. However, there are other ways to obtain energy offshore such as using tides and the sun. These types of farms are expensive and difficult to install and, therefore, we propose a combination of several renewable energies in one farm. The main ambition of this work is to try to reduce the installation and maintenance costs of the two types of offshore renewable energies by creating a structure capable of supporting the two types of turbines. To accomplish it, a theoretical study will be made, a brief state-of-the-art will be presented, the chosen items and the environment chosen for installation will be referred to, a prototype will be simulated using a multiphysics software and, finally, the results and conclusions will be presented, based on a Portuguese case study. How piezoelectric materials can enter offshore farms to increase efficiency is also referred to. The project proved to be possible of producing approximately 12.5 GWh of energy annually, more or less enough to supply 10 thousand homes. However, the installation of the piezoelectric materials did not prove to be viable as it is an expensive technology and does not produce a large amount of energy.

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Section: Wind Turbinesmentioning

confidence: 99%

“…The wind turbine's characteristics are usually related to the degree of air density. The energy produced by the wind is directly commensurate to the degree of air density [16].…”

Section: Wind Turbinesmentioning

confidence: 99%

How to Improve an Offshore Wind Station

Torres

Jesus²,

Lameirinhas

2022

Energies

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“…The efficiency can be also estimated as the ratio between electrical and wind energies in a certain time interval Δt. Indicating the measured WT output power as Pout, the efficiency can be obtained as [12]- [13]:…”

Section: Estimation Of Wt Efficiencymentioning

confidence: 99%

An Innovative Correction Method of Wind Speed for Efficiency Evaluation of Wind Turbines

et al. 2021

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The performance of horizontal axis Wind Turbines (WTs) is strongly affected by the wind speed entering in their rotor. Generally, this quantity is not available, because the wind speed is measured on the nacelle behind the turbine rotor, providing a lower value. Therefore, two correction methods are usually employed, requiring two input quantities: the wind speed on the back of the turbine nacelle and the wind speed measured by a meteorological mast close to the turbines under analysis. However, the presence of this station in wind farms is rare and the number of WTs in the wind farm is high. This paper proposes an innovative correction, named “Statistical Method” (SM), that evaluates the efficiency of WTs by estimating the wind speed entering in the WTs rotor. This method relies on the manufacturer power curve and the data measured by the WT anemometer only, thus having the possibility to be also applied in wind farms without a meteorological station. The effectiveness of such a method is discussed by comparing the results obtained by the standard methods implemented on two turbines (rated power = 1.5 MW and 2.5 MW) of a wind power plant (nominal power = 80 MW) in Southern Italy.

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“…It includes methods based on physical models and those based on mathematical statistics. The physical model method establishes a physical model of wind power output based on the aerodynamic principles of wind turbines, and then analyses the influence of external factors on wind power based on the physical model [12][13][14]. However, because of the complex relation between various factors and wind power output, it is difficult to establish an accurate physical model [15].…”

Section: Introductionmentioning

confidence: 99%

Correlation analysis of factors affecting wind power based on machine learning and Shapley value

Pang

Liu

2021

IET Energy Syst Integration

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An analysis of the impact of various factors on wind power can help grid dispatchers understand the characteristics of wind power output and improve the accuracy of wind power forecasting. A correlation analysis method of factors affecting wind power is proposed based on machine learning and the Shapley value. First, factors affecting wind power and the method of constructing wind power models based on machine learning are introduced. Then, to measure the influence of factors on wind power, the Shapley value is proposed based on the wind power model. In addition, calculation methods, properties, and application scenarios of the Shapley value are introduced. Finally, based on the actual data of a wind farm, the method is used to analyse environmental factors affecting wind power, and the main factors affecting the wind farm are determined. The experimental results show that the method can identify important factors affecting wind power and measure the complex non-linear relation between each environmental factor and wind power.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Evaluation of factors affecting wind turbine output power

Cited by 17 publications

References 12 publications

How to Improve an Offshore Wind Station

How to Improve an Offshore Wind Station

An Innovative Correction Method of Wind Speed for Efficiency Evaluation of Wind Turbines

Correlation analysis of factors affecting wind power based on machine learning and Shapley value

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