The Significance of Wind Turbines Layout Optimization on the Predicted Farm Energy Yield

被引：20

作者：

Al-Addous, Mohammad ^{[1
]}

Jaradat, Mustafa ^{[1
]}

Albatayneh, Aiman ^{[1
]}

Wellmann, Johannes ^{[2
]}

Al Hmidan, Sahil ^{[3
]}

机构：

[1] German Jordanian Univ, Dept Energy Engn, Amman Madaba St,POB 35247, Amman 11180, Jordan

[2] Tech Univ Berlin, Dept Environm Technol, Environm Proc Engn, Off KF 2,Str 17 Juni 135, D-10623 Berlin, Germany

[3] RSS, Natl Energy Res Ctr, POB 1438, Amman 11941, Jordan

来源：

ATMOSPHERE | 2020年 / 11卷 / 01期

关键词：

wind energy; optimization; WindFarm; 3D; wake effects; topography effects; PLACEMENT; ALGORITHM; SPEED;

D O I：

10.3390/atmos11010117

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Securing energy supply and diversifying the energy sources is one of the main goals of energy strategy for most countries. Due to climate change, wind energy is becoming increasingly important as a method of CO2-free energy generation. In this paper, a wind farm with five turbines located in Jerash, a city in northern Jordan, has been designed and analyzed. Optimization of wind farms is an important factor in the design stage to minimize the cost of wind energy to become more competitive and economically attractive. The analyses have been carried out using the WindFarm software to examine the significance of wind turbines' layouts (M, straight and arch shapes) and spacing on the final energy yield. In this research, arranging the turbines facing the main wind direction with five times rotor diameter distance between each turbine has been simulated, and has resulted in 22.75, 22.87 and 21.997 GWh/year for the M shape, Straight line and Arch shape, respectively. Whereas, reducing the distance between turbines to 2.5 times of the rotor diameter (D) resulted in a reduction of the wind farm energy yield to 22.68, 21.498 and 21.5463 GWh/year for the M shape, Straight line and Arch shape, respectively. The energetic efficiency gain for the optimized wind turbines compared to the modeled layouts regarding the distances between the wind turbines. The energetic efficiency gain has been in the range between 8.9% for 5D (rotor diameter) straight layout to 15.9% for 2.5D straight layout.

引用

页数：14

共 27 条

[11] Placement of wind turbines using genetic algorithms [J].

Grady, SA ;

Hussaini, MY ;

Abdullah, MM .

RENEWABLE ENERGY, 2005, 30 (02) :259-270

[12] Atmospheric stability and topography effects on wind turbine performance and wake properties in complex terrain [J].

Han, Xingxing ;

Liu, Deyou ;

Xu, Chang ;

Shen, Wen Zhong .

RENEWABLE ENERGY, 2018, 126 :640-651

[13] Wind farm layout optimization using self-informed genetic algorithm with information guided exploitation [J].

Ju, Xinglong ;

Liu, Feng .

APPLIED ENERGY, 2019, 248 :429-445

[14] Design of wind farm layout for maximum wind energy capture [J].

Kusiak, Andrew ;

Song, Zhe .

RENEWABLE ENERGY, 2010, 35 (03) :685-694

[15] Adaptive Robust Optimization With Dynamic Uncertainty Sets for Multi-Period Economic Dispatch Under Significant Wind [J].

Lorca, Alvaro ;

Sun, Xu Andy .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2015, 30 (04) :1702-1713

[16] Optimal placement of wind turbines in a wind park using Monte Carlo simulation [J].

Marmidis, Grigorios ;

Lazarou, Stavros ;

Pyrgloti, Eleftheria .

RENEWABLE ENERGY, 2008, 33 (07) :1455-1460

[17] OPTIMIZATION OF WIND TURBINE POSITIONING IN LARGE WINDFARMS BY MEANS OF A GENETIC ALGORITHM [J].

MOSETTI, G ;

POLONI, C ;

DIVIACCO, B .

JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 1994, 51 (01) :105-116

[18] Assessing the energy benefit of using a wind turbine micro-siting model [J].

Parada, Leandro ;

Herrera, Carlos ;

Flores, Paulo ;

Parada, Victor .

RENEWABLE ENERGY, 2018, 118 :591-601

[19] Wind farm layout optimization using a Gaussian-based wake model [J].

Parada, Leandro ;

Herrera, Carlos ;

Flores, Paulo ;

Parada, Victor .

RENEWABLE ENERGY, 2017, 107 :531-541

[20] Wind power forecasting for a real onshore wind farm on complex terrain using WRF high resolution simulations [J].

Prosper, Miguel A. ;

Otero-Casal, Carlos ;

Canoura Fernandez, Felipe ;

Miguez-Macho, Gonzalo .

RENEWABLE ENERGY, 2019, 135 :674-686

← 1 2 3 →