Estimation of Long-Term Concentrations Using a “Universal” Wind Speed Distribution

Luna, R.; Church, H.W.

doi:10.1175/1520-0450(1974)013<0910:eoltcu>2.0.co;2

Cited by 71 publications

(29 citation statements)

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“…However, the wind power forecast is relatively complex, and the forecast errors cannot be avoided. Generally, the wind speed can be approximated as the Gamma distribution [30], inverse Gaussian [31], log-normal [32], and Weibull [33][34][35][36]. Alternatively, copula theory has recently been applied to wind speed and wind power as a way of modeling nonlinear dependence structures [37].…”

Section: Wind Power Generation Modelmentioning

confidence: 99%

Energy Trading and Pricing in Microgrids with Uncertain Energy Supply: A Three-Stage Hierarchical Game Approach

Yang

et al. 2017

Energies

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This paper studies an energy trading and pricing problem for microgrids with uncertain energy supply. The energy provider with the renewable energy (RE) generation (wind power) determines the energy purchase from the electricity markets and the pricing strategy for consumers to maximize its profit, and then the consumers determine their energy demands to maximize their payoffs. The hierarchical game is established between the energy provider and the consumers. The energy provider is the leader and the consumers are the followers in the hierarchical game. We consider two types of consumers according to their response to the price, i.e., the price-taking consumers and the price-anticipating consumers. We derive the equilibrium point of the hierarchical game through the backward induction method. Comparing the two types of consumers, we study the influence of the types of consumers on the equilibrium point. In particular, the uncertainty of the energy supply from the energy provider is considered. Simulation results show that the energy provider can obtain more profit using the proposed decision-making scheme.

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Section: Wind Power Generation Modelmentioning

confidence: 99%

Energy Trading and Pricing in Microgrids with Uncertain Energy Supply: A Three-Stage Hierarchical Game Approach

Yang

et al. 2017

Energies

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“…This can be obtained using the probability distribution of wind speed, direction and stresses. Literature is also available on the use of lognormal distribution for long term wind speed [31][32][33]. In this paper, we assumed a lognormal distribution for the wind speed data in order to simplify the formulation in the Bayesian model while maintaining good fit to the observed data, but it can be changed to any other distribution if necessary.…”

Section: Probability Distributions Of Wind Speed Direction and Stressmentioning

confidence: 99%

Effect of uncertainties in wind speed and direction on the fatigue damage of long-span bridges

Alduse

Jung

Vanli

et al. 2015

Engineering Structures

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“…[14] compared fit of a Rayleigh distribution and another Weibull distribution to wind speed data and showed that the Weibull model provided a better fit. In [15], a wind speed distribution was shown to be satisfactorily described by a Lognormal distribution. In [16] Weibull and Lognormal distributions were used to fit wind speed frequencies and concluded that the Weibull distribution better fit the data.…”

Section: Introductionmentioning

confidence: 99%

Bayesian predictive models for Rayleigh wind speed

Shahirinia

Hajizadeh

2017

2017 IEEE 17th International Conference on Ubiquitous Wireless Broadband (ICUWB)

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Abstract-One of the major challenges with the increase in wind power generation is the uncertain nature of wind speed. So far the uncertainty about wind speed has been presented through probability distributions. Also the existing models that consider the uncertainty of the wind speed primarily view the distributions of the wind speed over a wind farm as being homogeneous. However, the uncertainty about these wind speed models has not yet been considered. In this paper the Bayesian approach to taking into account the uncertainty inherent in the wind speed model has been presented. The proposed Bayesian predictive model of the wind speed aggregates the nonhomogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines' locations in a wind farm. More specifically, instead of using a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented.

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Estimation of Long-Term Concentrations Using a “Universal” Wind Speed Distribution

Cited by 71 publications

References 0 publications

Energy Trading and Pricing in Microgrids with Uncertain Energy Supply: A Three-Stage Hierarchical Game Approach

Energy Trading and Pricing in Microgrids with Uncertain Energy Supply: A Three-Stage Hierarchical Game Approach

Effect of uncertainties in wind speed and direction on the fatigue damage of long-span bridges

Bayesian predictive models for Rayleigh wind speed

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