Optimum turbine-site matching

Albadi, Mohammed; El-Saadany, Ehab F.

doi:10.1016/j.energy.2010.04.049

Cited by 58 publications

(39 citation statements)

References 13 publications

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“…The obtained results can be used to perform wind park project and confirm that the Gulf of Tunis has promising wind energy potential. A new formulation for the turbine-site matching problem was presented by [7], based on wind speed characteristics at any site, the power performance curve parameters of any pitch-regulated wind turbine, as well as turbine size and tower height. The results revealed that higher tower heights are not always desirable for optimality.…”

Section: Introductionmentioning

confidence: 99%

Potential of Wind Speed for Wind Power Generation In Perlis, Northern Malaysia

et al. 2011

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Abstrak Makalah ini menyajikan analisa karakteristik-karakteristik kecepatan angin di Keywords: weibull distribution function, wind power generation, wind speed IntroductionRenewable energy has an increasing role in achieving the goals of sustainable development, energy security and environmental protection. Nowadays, it has been recognized as one of the most promising clean energy over the world because of its falling cost, while other renewable energy technologies are becoming more expensiveWind energy is one of renewable energy which produced by continuously blowing wind and can be captured using wind turbines that convert kinetic energy from wind into mechanical energy and then into electrical energy [3]. Today, wind energy is widely used to produce electricity in many countries such as Denmark, Spain, Germany, United States, and India [4].A lot of researchers have been studying the wind speed characteristics and its potential as a wind power generation in many countries worlwide. Six kinds of numerical methods for estimating Weibull parameters were reviewed by [5]; i.e. the moment, empirical, graphical, maximum likelihood, modified maximum likelihood, and energy pattern factor method. The result showed that the maximum likelihood modified maximum likelihood and moment methods present relatively more excellent ability throughout the simulation test. From analysis of actual data, it is found that if wind speed distribution matches well with Weibull function, the six methods are applicable, but if not, the maximum likelihood method performs best followed by the modified maximum likelihood and moment methods, based on double checks including

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Section: Introductionmentioning

confidence: 99%

Potential of Wind Speed for Wind Power Generation In Perlis, Northern Malaysia

et al. 2011

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“…A cost model for the effect of hub height on ICC [14] was adopted, in which the tower and related foundation costs increase by 1% with a 2% increase in h for the base-case h = 80 m. Finally, ICC can be expressed as follows: …”

Section: Iccmentioning

confidence: 99%

“…Though COE considers the initial capital cost as well as energy production, the net profit is not calculated; thus, it cannot judge the economic feasibility. More recently, Albadi et al [14] proposed the turbine-site matching index (TSMI) as an objective function for optimizing the wind turbine systems. Chen et al investigated the wind turbine tower height matching problem in the wind farm [15] and developed an iteration method for the same problem [16] using TSMI.…”

Section: Introductionmentioning

confidence: 99%

“…Although several studies were reported on optimizing the wind turbine hub height [9][10][11][12][13][14][15][16], there were the limitations that the economic feasibility could not be ensured as the net profit was not considered in the objective function. Al-Hadhrami [9] recommended suitable hub height for small wind turbines under 80 kW based on Capacity Factor (CF).…”

Section: Introductionmentioning

confidence: 99%

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Optimum hub height of a wind turbine for maximizing annual net profit

Lee

Kim

Lee

2015

Energy Conversion and Management

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“…Utilization of renewable energy sources (RES) for rural communities has been studied extensively with the conclusion that RES could be both economical and environmental friendly if employed for electricity generation in such rural areas. 2,3 Various studies have modeled the theoretical site-matching wind turbine for any area under study, [4][5][6] in addition to modeling site solar insolation on optimum tilt angles. 7 The economics of deploying such REES are mainly based on cost estimates and the use of levelized cost of electricity (LCOE) produced from these systems.…”

Section: Journal Of Renewable and Sustainablementioning

confidence: 99%

Comparative study of economic viability of rural electrification using renewable energy resources versus diesel generator option in Saudi Arabia

Bawah

Addoweesh

Eltamaly

2013

Journal of Renewable and Sustainable Energy

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The objective of this paper is to assess the economic viability of Saudi Arabia's renewable energy resources in electricity production in the rural and remote areas as against the use of diesel generators (DG). The methodology employed is to pick an existing isolated DG electric station for a rural community and assess the levelized cost of energy (LCOE) generated for incremental generation by adding either DG, wind electric conversion system(WECS), or solar Photo Voltaic (PV) electric system. Cost figures are derived from current technology price indices and consultancies studies as contained in the National Renewable Energy Laboratory cost report of November 2012. The existing power station of Addfa in the Southern region is analyzed based on the requirement to increase its current capacity to cater for surrounding smaller communities. An annual extra energy requirement of 4 GWh is to be met by scenarios of using DG, WECS, PV or a hybrid system. Two ownership structures are considered namely a public utility that pays no tax and a private independent power producer (IPP) that pays tax. Both the constant and current LCOE generated are determined for each ownership structure. The results indicate that the WECS is the first investment choice with a constant LCOE of $0.0922/kWh and $0.1090/kWh for the public utility and the IPP, respectively. The DG is the second choice with LCOE of $0.1082/kWh and $0.1175/kWh, the third is a hybrid DG plus WECS with LCOE of $0.1102/kWh and $0.1234/kWh for each ownership structure, respectively. Finally, the PV electric system ranks fourth with LCOE of $0.2791/kWh and $0.3279/kWh, respectively. The results of sensitivity analysis show that these values of LCOE are more sensitive to the initial capital cost and less sensitive to the operation and management costs.

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Optimum turbine-site matching

Cited by 58 publications

References 13 publications

Potential of Wind Speed for Wind Power Generation In Perlis, Northern Malaysia

Potential of Wind Speed for Wind Power Generation In Perlis, Northern Malaysia

Optimum hub height of a wind turbine for maximizing annual net profit

Comparative study of economic viability of rural electrification using renewable energy resources versus diesel generator option in Saudi Arabia

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