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

Al-Addous, Mohammad; Jaradat, Mustafa; Albatayneh, Aiman; Wellmann, Johannes; Hmidan, Sahil Al

doi:10.3390/atmos11010117

Cited by 20 publications

(12 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This elevation difference (2184 m) is a positive factor for wind energy generation in most regions because it works to change the air pressure from one region to another. Thus, the flow of winds at various speeds and densities [54].…”

Section: Area Of Interest (Aoi)mentioning

confidence: 99%

Establishing Regional Power Sustainability and Feasibility Using Wind Farm Land-Use Optimization

Gharaibeh

Al-Shboul

Al‐Rawabdeh

et al. 2021

Land

View full text Add to dashboard Cite

Wind-farm planning optimization is important for decision-making concerning regional energy planning in developing countries. This process is governed by restrictions on site selection based on land suitability metric variables, wind turbine technology variables, and land-use governing criteria. This study aims to create a framework for land appropriation strategies for locating optimum sites suitable for wind farms. It is using Jordan as an Area of Interest (AOI), where the scope is to illustrate how this framework will employ wind turbine energy to positively enhance the national Gross Domestic Product (GDP). The methodology employs thirteen GIS thematic layers with a 250-m spatial resolution to substantiate how site-specific criteria, turbine type, and turbine hub height variables are determining factors in the optimal solution. This method involves selecting relevant factors, database construction, data layer generation and preparation, numerical ranking and weighting of each factor, and computation of the potential wind farm locations map by overlaying all the thematic GIS layers. The results showed that the establishment of wind farms would not only meet the AOI’s growing energy needs, rather exceed them to generating income for the developing nation. The results of the feasibility study will boost the national GDP by 3.4%; where, for example, one governorate alone could produce 274.3% of the total required national consumption at a turbine hub height of 50 m. The study attests to a valuable framework that can be implemented elsewhere to establish regional power sustainability and feasibility for other nations. The results show that an added land-use layer indicating the potential value of land in terms of its suitability for establishing wind farms should be considered in future sustainable regional planning studies when considering networks for smart cities, industrial cities, smart agriculture, and new agglomerations.

show abstract

Section: Area Of Interest (Aoi)mentioning

confidence: 99%

Establishing Regional Power Sustainability and Feasibility Using Wind Farm Land-Use Optimization

Gharaibeh

Al-Shboul

Al‐Rawabdeh

et al. 2021

Land

View full text Add to dashboard Cite

show abstract

“…As part of efforts to maximize efficiency and energy production and to reduce installation costs, proper quantities of wind power plants and their deployment remain important issues to be further investigated [4]. Further developments have been made in recent years to optimize wind turbines in larger wind farms [5].…”

Section: Introductionmentioning

confidence: 99%

On the Development of a Metamodel and Design Support Excel Automation Program for Offshore Wind Farm Layout Optimization

Shin

Baek²,

Rhee

2021

JMSE

View full text Add to dashboard Cite

In this study, a metamodel of an optimal arrangement of wind turbines was developed to maximize the energy produced by minimizing the energy loss due to wakes in a limited space when designing a wind farm. Metamodeling or surrogate modeling techniques are often used to replace expensive simulations or physical experiments of engineering problems. Given a training set, you can construct a set of metamodels. This metamodel provided insight into the correlation between wind farm geometry and the corresponding turbine layout (maximizing energy production), thereby optimizing the area of the wind farm required to maximize wind turbine capacity. In addition, a design support Microsoft Excel program was developed to quickly and easily calculate the annual energy production forecast considering the wake effect, as well as to confirm the prediction suitability, the annual energy production (AEP) analysis result of the wind farm, and the calculation result from existing commercial software were compared and verified.

show abstract

Section: Introductionmentioning

confidence: 99%

“…Diversifying energy sources and securing energy supplies are key energy strategy targets for many countries [1]. Due to climate change, wind energy has become more and more important for power generation without carbon dioxide emissions [1]. Offshore wind power is a good opportunity for South Korea, providing opportunities to accelerate power generation without the use of fossil fuels or nuclear power generation [2].…”

Section: Introductionmentioning

confidence: 99%

Wind Farm Layout Optimization Using a Metamodel and EA/PSO Algorithm in Korea Offshore

Shin

Baek²,

Rhee

2020

Energies

View full text Add to dashboard Cite

This paper examines the solution to the problem of turbine arrangement in offshore wind farms. The two main objectives of offshore wind farm planning are to minimize wake loss and maximize annual energy production (AEP). There is more wind with less turbulence offshore compared with an onshore case, which drives the development of the offshore wind farm worldwide. South Korea’s offshore wind farms, which are deep in water and cannot be installed far off the coast, are affected by land complex terrain. Thus, domestic offshore wind farms should consider the separation distance from the coastline as a major variable depending on the topography and marine environmental characteristics. As a case study, a 60 MW offshore wind farm was optimized for the coast of the Busan Metropolitan City. For the analysis of wind conditions in the candidate site, wind conditions data from the meteorological tower and Ganjeolgot AWS at Gori offshore were used from 2001 to 2018. The optimization procedure is performed by evolutionary algorithm (EA) and particle swarm optimization (PSO) algorithm with the purpose of maximizing the AEP while minimizing the total wake loss. The optimization procedure can be applied to the optimized placement of WTs within a wind farm and can be extended for a variety of wind conditions and wind farm capacity. The results of the optimization were predicted to be 172,437 MWh/year under the Gori offshore wind potential, turbine layout optimization, and an annual utilization rate of 26.5%. This could convert 4.6% of electricity consumption in the Busan Metropolitan City region in 2019 in offshore wind farms.

show abstract

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

Cited by 20 publications

References 24 publications

Establishing Regional Power Sustainability and Feasibility Using Wind Farm Land-Use Optimization

Establishing Regional Power Sustainability and Feasibility Using Wind Farm Land-Use Optimization

On the Development of a Metamodel and Design Support Excel Automation Program for Offshore Wind Farm Layout Optimization

Wind Farm Layout Optimization Using a Metamodel and EA/PSO Algorithm in Korea Offshore

Contact Info

Product

Resources

About