WIND ENERGY POTENTIAL ASSESSMENT BASED ON WIND DIRECTION MODELLING AND MACHINE LEARNING

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27730%2F16%3A86100168" target="_blank" >RIV/61989100:27730/16:86100168 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27360/16:86100168 RIV/61989100:27240/16:86100168
Result on the web
<a href="http://www.nnw.cz/doi/2016/NNW.2016.26.030.pdf" target="_blank" >http://www.nnw.cz/doi/2016/NNW.2016.26.030.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2016.26.030" target="_blank" >10.14311/NNW.2016.26.030</a>

Result language
angličtina
Original language name
WIND ENERGY POTENTIAL ASSESSMENT BASED ON WIND DIRECTION MODELLING AND MACHINE LEARNING
Original language description
Precise wind energy potential assessment is vital for wind energy generation and planning and development of new wind power plants. This work proposes and evaluates a novel two-stage method for location-specific wind energy potential assessment. It combines accurate statistical modelling of annual wind direction distribution in a given location with supervised machine learning of efficient estimators that can approximate energy efficiency coefficients from the parameters of optimized statistical wind direction models. The statistical models are optimized using differential evolution and energy efficiency is approximated by evolutionary fuzzy rules.
Czech name
—
Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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