Abstract
Wind energy is a vital part of Australia’s energy mix. The first step in a wind power project at a particular site is to assess the wind resource potential and feasibility for wind energy production. Research on wind potential and statistical analysis has been done throughout the world. Currently, recent potential wind studies are lacking, especially in New South Wales (NSW), Australia. This study highlighted the feasibility of wind potential at four sites in NSW, namely Ballina, Merriwa, Deniliquin, and the Bega region. The type of wind speed distribution function dramatically affects the output of the available wind energy and wind turbine performance at a particular site. Therefore, the accuracy of four probability density functions was evaluated, namely Rayleigh, Weibull, Gamma, and Lognormal distributions. The outcomes showed Weibull provided the most accurate distribution. The annual average scale and shape parameters of Weibull distribution varied between 2.935–5.042 m/s and 1.137–2.096, respectively. The maximum shape and scale factors were at Deniliquin, while the minimum shape and scale factors were at Bega area. Assessment of power density indicated that Deniliquin had a marginal wind speed resource, while Ballina, Bega, and Merriwa had poor wind resources.
| Original language | English |
|---|---|
| Pages (from-to) | 194-211 |
| Number of pages | 18 |
| Journal | Energy Sources, Part A: Recovery, Utilization and Environmental Effects |
| Volume | 47 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2025 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Free Keywords
- Probability density function
- statistical analysis
- Weibull distribution
- wind energy
- wind potential
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Nuclear Energy and Engineering
- Fuel Technology
- Energy Engineering and Power Technology
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