Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming

Kuo, Jim; Romero, David A.; Beck, J. Christopher; Amón, Cristina H.

doi:10.1016/j.apenergy.2016.06.085

Cited by 90 publications

(38 citation statements)

References 47 publications

(74 reference statements)

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“…Wake effect is the reduction of wind velocity and increased turbulence behind a wind turbine [13,14]. Wake effect can decrease power output of a wind farm by 10-20% per annum [12,[15][16][17]. Moreover, turbulence resulted from wake, increases dynamic loading on downstream turbines which can precipitate material fatigue [13,[18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

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Optimization of wind farm layout considering wake effect and multiple parameters

Markarian

Fazelpour

Markarian

2019

Env Prog and Sustain Energy

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The output power of wind farms in real world applications is lower than the theoretical output which is largely due to wake effect. So as to maximize the output power, the wake effect of upstream wind turbines on downstream ones should be attenuated. Thus, arrangement of wind turbines in a wind farm is an essential issue that needs to be tackled. This study pursues the aim of finding an optimal layout. Initially, Jensen wake model is applied to simulate the wake effect. Then, genetic algorithm is employed to optimize the wind farm layout considering multiple factors that include different hub heights, rotor diameters, variable induction factors, power and capacity factor curves. Three cases including constant wind–constant direction, constant wind–variable direction and variable wind–variable direction are studied and compared with previous studies. The results indicate that the efficiency of the wind farm for case 1 is 96.71% which is a high record comparing to the previous literature. For Case 2 and 3, the annual wind farm capacity factor (CF) is found to be 97.96 and 97.51%. The power output of Case 1, 2, and 3 are 5.6855 × 108 kWh, 5.6694 × 108 kWh, and 4.5572 × 108 kWh, respectively. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13146, 2019

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Section: Introductionmentioning

confidence: 99%

“…The results proved the accuracy of the advanced model compared with previous models. To optimize layout of wind farms on complex terrains, Kuo et al introduced a computational fluid dynamics method combined with mix-integer programming [33]. The introduced method was applied to a wind farm located in Quebec, Canada.…”

Section: Introductionmentioning

confidence: 99%

Optimization of wind farm layout considering wake effect and multiple parameters

Markarian

Fazelpour

Markarian

2019

Env Prog and Sustain Energy

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“…Several authors [83,84] explored the potential of unconventional methods of incorporation of wind energy systems into the built environment. Park et al [83] proposed and assessed a BIWT systems incorporated into the building façade which combines a series of guide vanes to re-direct and accelerate the wind into a rotor.…”

Section: Building Scalementioning

confidence: 99%

“…The results showed that the system can accelerate the wind velocity to satisfactory levels and, therefore, increases power production. Hassanli et al [84] used CFD modelling to assess the characteristics of the flow in a Double-Skin Façade (DSF) system with openings for harvesting wind energy in high rise buildings. The model was assessed with wind tunnel experiments and a good agreement was found between the results (15% discrepancy).…”

Section: Building Scalementioning

confidence: 99%

“…Kuo et al [84] proposed an algorithm that combines mixed-integer programming (MIP) and Computational Fluid Dynamics (CFD) to optimise wind farm layouts for complex topographies. The MIP solvers' ability to search solutions was essential for capturing the effects of optimised wake deficit projections on the quality of wind farm layout solutions.…”

Section: Large Scalementioning

confidence: 99%

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A Review of Numerical Modelling of Multi-Scale Wind Turbines and Their Environment

et al. 2018

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Abstract:Global demand for energy continues to increase rapidly, due to economic and population growth, especially for increasing market economies. These lead to challenges and worries about energy security that can increase as more users need more energy resources. Also, higher consumption of fossil fuels leads to more greenhouse gas emissions, which contribute to global warming. Moreover, there are still more people without access to electricity. Several studies have reported that one of the rapidly developing source of power is wind energy and with declining costs due to technology and manufacturing advancements and concerns over energy security and environmental issues, the trend is predicted to continue. As a result, tools and methods to simulate and optimize wind energy technologies must also continue to advance. This paper reviews the most recently published works in Computational Fluid Dynamic (CFD) simulations of micro to small wind turbines, building integrated with wind turbines, and wind turbines installed in wind farms. In addition, the existing limitations and complications included with the wind energy system modelling were examined and issues that needs further work are highlighted. This study investigated the current development of CFD modelling of wind energy systems. Studies on aerodynamic interaction among the atmospheric boundary layer or wind farm terrain and the turbine rotor and their wakes were investigated. Furthermore, CFD combined with other tools such as blade element momentum were examined. Keywords:Computational Fluid Dynamic (CFD); micro to small wind turbine; building integrated with wind turbine; wind farm; aerodynamic interaction; wind energy systems; atmospheric boundary layer (ABL); blade element momentum (BEM)

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Optimizing Wind Farm Layouts

Tang¹

2021

Handbook of Wind Energy Aerodynamics

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Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming

Cited by 90 publications

References 47 publications

Optimization of wind farm layout considering wake effect and multiple parameters

Optimization of wind farm layout considering wake effect and multiple parameters

A Review of Numerical Modelling of Multi-Scale Wind Turbines and Their Environment

Optimizing Wind Farm Layouts

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