Uncertainty analysis of wind energy potential assessment

Kwon, Soon-Duck

doi:10.1016/j.apenergy.2009.08.038

Cited by 206 publications

(92 citation statements)

References 15 publications

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“…More so, where others present a better fit (e.g., the nonparametric kernel density function [47], they could not be used to determine the two important wind speeds for wind farm evaluation or carry out further technical analyses. The statistical significance of the Weibull results has also been the best [40,41,[48][49][50].…”

Section: Discussionmentioning

confidence: 99%

Wind Energy Study and Energy Cost of Wind Electricity Generation in Nigeria: Past and Recent Results and a Case Study for South West Nigeria

et al. 2014

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The study assessed the wind energy potential of ten selected sites in the south western region of Nigeria and carried out a cost benefit analysis of wind power generation at those sites. Twenty four years ' (1987 to 2010) wind speed data at 10 m height obtained from the Nigerian meteorological agency were employed to classify the sites wind profiles for electricity generation. The energy cost analysis of generating wind electricity from the sites was also carried out. The outcome showed that sites in Lagos and Oyo States were adequately suited for large scale generation with average wind speeds ranged between 2.9 and 5.8 m/s. Those from other sites may be suitable for small scale generation or as wind farms, with several small turbines connected together, to generate large enough wind power. The turbine matching results shows that turbines cut-in and rated wind speeds of between 2.0 and 3.0 m/s, and between 10 and 12.0 m/s respectively will be very suited to OPEN ACCESSEnergies 2014, 7 8509 all the sites, particularly those in locations outside Lagos and Oyo States. The energy cost analysis shows that generation cost can be as low as 0.02 €/kWh and as high as 5.03/kWh, depending on the turbine model employed.

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Section: Discussionmentioning

confidence: 99%

Wind Energy Study and Energy Cost of Wind Electricity Generation in Nigeria: Past and Recent Results and a Case Study for South West Nigeria

et al. 2014

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“…Forexample, the distributions whose null speed percentage is higher or in the case of bimodal distributions [4]. Besides, in estimating the Weibull parameters, the uncertainty is inevitable, essentially when there is not enough historic data [18]. Some researchers have been conducted to ameliorate the precision of wind modeling by Weibull, adopting Neural Network approach.…”

Section: Resultsmentioning

confidence: 99%

“…In the case where is attempted to model the wind speed in a site where there is no enough data, the Measure-CorrelatePredict method (MCP) is often used [18]. The MCP method based on the ratio of the standard deviations, is used to estimate the long-term wind data at the target site from the wind data at the reference site.…”

Section: Comparative Methods Of Wind Energy Estimationmentioning

confidence: 99%

Horizontal Extrapolation of Wind Speed Distribution Using Neural Network for Wind Resource Assessment

2017

IJSR

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Abstract:To evaluate the wind potential on a site for future wind energy project, an accurate representation of the wind speed distribution is required. However, due to the lack of observations, wind engineers are conducted to use some statistical tools to estimate the characteristics of wind by the measurements from a nearby reference or data obtained from a short period. In this work, we aim at applying an information processing paradigm that is inspired by biological neurons, formal neurons, for the assessment of wind speed distribution. Two different learning algorithms are used so as to generate Artificial Neural Network with one hidden layer. Results prove that learning by means of Bayesian regularization, in comparison with Levenberg-Marquardt learning algorithm, gives the best performance. In addition, the proposed network allows significant results in horizontal wind extrapolation.

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“…Some of them include normal, lognormal, Rayleigh and Weibull probability distributions [17,18]. It has been found that among probability distribution functions used by many researchers, the Weibull distribution is most accurate and adequate in wind analyzing and interpreting the actual wind speed data and in predicting the characteristics of prevailing wind profile [17,19] .…”

Section: The Three Parameter Weibull Distribution Model Of Wind Powermentioning

confidence: 99%

Probabilistic model of Wind Power Ramp Events Based On Moving Ratio Analysis

Liu¹,

Wang²

2016

Proceedings of the 2016 5th International Conference on Energy and Environmental Protection (ICEEP 2016)

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Abstract. Description of probability distribution characteristics of wind power ramp events is always a challenge in grid-connected wind power operation analysis. In this paper, a moving ratio based approach of wind power ramp events is introduced and an probability model is described for the wind ramp events. The proposed model is useful to estimate the relationship between power ramp events and the variability of the wind power. The proposed model is able to satisfactorily approximate the actual distribution of wind power ramp events . It is shown that the linear difference based ramp distribution can be calculated using the proposed moving ratio based approach. The proposed model can be an effective tool in planning for wind power ramp control.

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Uncertainty analysis of wind energy potential assessment

Cited by 206 publications

References 15 publications

Wind Energy Study and Energy Cost of Wind Electricity Generation in Nigeria: Past and Recent Results and a Case Study for South West Nigeria

Wind Energy Study and Energy Cost of Wind Electricity Generation in Nigeria: Past and Recent Results and a Case Study for South West Nigeria

Horizontal Extrapolation of Wind Speed Distribution Using Neural Network for Wind Resource Assessment

Probabilistic model of Wind Power Ramp Events Based On Moving Ratio Analysis

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