Evaluating wind power density models and their statistical properties

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Information about the wind power df(density function) is very important when measuring the wind energy potential for a specific area. Usually, the wind power df provides knowledge about the mean power, which is an indicator of the energy potential. However, the mean power does not describe well the characteristics of power density. Thus, by knowing information about other statistical properties, such as standard deviation, skewness and kurtosis, better insight about the characteristics and properties of power density can be obtained. This study proposes a method to derive a wind power density model and its statistical properties particularly from well-known dfs, namely, the Weibull, Gamma and Inverse Gamma dfs. Applying the method of transformation and Monte Carlo integration has been discussed to address the difficulty of finding the different statistical properties of power density. In addition, an application of the proposed method is demonstrated by a case study that involves wind speed data from several stations in Malaysia.

Original languageEnglish
Pages (from-to)533-541
Number of pages9
JournalEnergy
Volume84
DOIs
Publication statusPublished - 1 May 2015

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Wind power
Probability density function
Potential energy

Keywords

  • Statistical modeling
  • Wind energy
  • Wind power density
  • Wind speed probability distribution

ASJC Scopus subject areas

  • Energy(all)
  • Pollution

Cite this

Evaluating wind power density models and their statistical properties. / Masseran, Nurulkamal.

In: Energy, Vol. 84, 01.05.2015, p. 533-541.

Research output: Contribution to journalArticle

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