Researchers Evaluate Wind Energy Potential at Trebević Using Advanced Statistical Methods
A new study published in the journal Energy Reports examines the wind power potential at Trebević, a mountainous area near Sarajevo in Bosnia and Herzegovina. The research, led by Rejhana Blažević along with co-authors Ismira Muminović, Ehlimana Jugo, and Halima Hadžiahmetović, applies multiple statistical approaches to estimate Weibull distribution parameters from local wind data. The work provides concrete insights for renewable energy planning in the Western Balkans region.
The full paper is available at https://www.sciencedirect.com/science/article/pii/S2352484726004154.
Background on Wind Resource Assessment in Bosnia and Herzegovina
Bosnia and Herzegovina has identified renewable energy expansion as a strategic priority to meet European Union integration goals and reduce reliance on imported fossil fuels. Mountainous terrain such as Trebević offers promising wind regimes, yet detailed site-specific assessments remain limited. The current study addresses this gap by collecting and analysing high-resolution wind measurements over an extended period.
Wind resource evaluation typically begins with long-term anemometer data. Researchers then fit the Weibull probability density function, which is widely used in the wind energy industry because it accurately models the distribution of wind speeds. The two key Weibull parameters are the shape factor (k) and the scale factor (c). Different statistical estimators can produce slightly varying results, so the study compares several established methods to identify the most reliable approach for this location.
Statistical Methods Applied in the Trebević Case Study
The authors tested multiple techniques for estimating Weibull parameters, including the maximum likelihood method, the energy pattern factor method, and graphical approaches. Each method has distinct advantages: maximum likelihood is statistically robust for large datasets, while the energy pattern factor method directly incorporates power density considerations.
By applying these methods side by side, the research team quantified differences in estimated power density and annual energy production. The comparison highlights how method selection influences project feasibility assessments and financing decisions for potential wind farms.
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Key Findings from the Trebević Analysis
Results indicate moderate to good wind resources at the site, with seasonal variations that align with regional climate patterns. The study reports that certain estimators consistently yielded higher shape factors, suggesting a narrower wind speed distribution than others. These nuances matter when developers model turbine performance and revenue streams.
The research also examines how terrain effects and measurement height influence outcomes. Data collected at multiple elevations helped refine vertical wind shear profiles, improving the accuracy of extrapolations to hub heights typical of modern turbines.
Implications for Regional Energy Policy and Investment
The Trebević assessment contributes to Bosnia and Herzegovina’s broader renewable energy roadmap. Policymakers can use the findings to prioritise sites for detailed feasibility studies and to design incentive schemes that attract private investment. Accurate resource mapping reduces project risk and supports grid integration planning.
International development banks and European funding programmes often require robust wind data before committing capital. This peer-reviewed study supplies the type of evidence needed to unlock such support.
Opportunities for Academic Collaboration and Further Research
The publication opens avenues for cross-border research partnerships. Universities in the region could extend the dataset with additional meteorological stations or integrate machine-learning techniques to improve short-term wind forecasting. Comparative studies with neighbouring countries would strengthen understanding of Balkan wind regimes.
PhD candidates and postdoctoral researchers interested in renewable energy modelling will find the methodological framework useful as a benchmark. The open discussion of estimator performance provides a foundation for methodological refinements.
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Connection to Broader Academic and Career Pathways
Research of this nature directly supports the growth of specialised expertise in wind energy engineering and atmospheric science. Institutions seeking faculty or research staff with experience in statistical wind modelling may reference this work when recruiting. Early-career researchers can build on the dataset for thesis projects or industry collaborations.
AcademicJobs.com maintains listings for positions in renewable energy research and higher education roles that align with these emerging skill sets. Professionals exploring opportunities in sustainable energy should monitor postings in related fields.
Future Outlook for Wind Energy Research in the Western Balkans
As climate targets tighten, demand for high-quality wind resource assessments will increase. The Trebević study demonstrates the value of rigorous statistical comparison and site-specific analysis. Continued investment in measurement infrastructure and open data sharing will accelerate progress across the region.
Future work could incorporate climate change projections to assess long-term viability or combine wind data with solar and storage modelling for hybrid systems. The foundation laid by Blažević and colleagues positions Trebević as a reference site for such integrated studies.
