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Wind Resource and Wind Power Generation Assessment for Education in Engineering

doi: 10.3390/su13052444
handle: 10578/41263
This paper proposes a practical approach to assess wind energy resource and calculate annual energy production for use on university courses in engineering. To this end, two practical exercises were designed in the open-source software GNU Octave (compatible with MATLAB) using both synthetic and field data. The script used to generate the synthetic data as well as those created to develop the practical exercises are included for the benefit of other educational bodies. With the first exercise the students learn how to characterize the wind resource at the wind turbine hub height and adjust it to the Weibull distribution. Two examples are included in this exercise: one with an appropriate fit and another where the Weibull distribution does not fit properly to the generated data. Furthermore, in this exercise, field data (gathered with a LiDAR remote sensing device) is also used to calculate shear exponents for a proper characterisation of the wind profile. The second exercise consists of the calculation of the annual energy production of a wind power plant, where the students can assess the influence of different factors (wind speed, rotor diameter, rated power, etc.) in the project. The exercises proposed can easily be implemented through either in-class or online teaching modes.
Environmental effects of industries and plants, engineering education, TJ807-830, Energy education, sustainability, TD194-195, renewable energy, Engineering education, Renewable energy sources, Environmental sciences, Sustainability, energy education, GE1-350
Environmental effects of industries and plants, engineering education, TJ807-830, Energy education, sustainability, TD194-195, renewable energy, Engineering education, Renewable energy sources, Environmental sciences, Sustainability, energy education, GE1-350
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).14 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
