Wind Speed Forecast Correction Models using Polynomial Neural Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86095960" target="_blank" >RIV/61989100:27240/15:86095960 - isvavai.cz</a>

Result on the web

<a href="http://www.sciencedirect.com/science/article/pii/S0960148115003341" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0960148115003341</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.renene.2015.04.054" target="_blank" >10.1016/j.renene.2015.04.054</a>

Result language

angličtina

Original language name

Wind Speed Forecast Correction Models using Polynomial Neural Networks

Original language description

Accurate short-term wind speed forecasting is important for the planning of a renewable energy power generation and utilization, especially in grid systems. In meteorology it is usual to improve the forecasts by means of some post-processing methods using local measurements and weather prediction model outputs. Neural networks, trained with local real data observations can improve short-term wind speed forecasts with respect to meso-scale numerical meteorological model outcomes of the same data types inthe majority of cases. Large-scale forecast models are based on the numerical integration of differential equation systems, which can describe atmospheric circulation processes on account of global meteorological observations. Several layer 3D complex models, which involve a large number of matrix variables, cannot exactly describe conditions near the ground, highly influenced by a landscape relief, coast, structure and other factors. Polynomial neural networks can form and solve genera

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

IN - Informatics

OECD FORD branch

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Project

<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2015

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Renewable Energy

ISSN

0960-1481

e-ISSN

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Volume of the periodical

83

Issue of the periodical within the volume

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Country of publishing house

GB - UNITED KINGDOM

Number of pages

9

Pages from-to

998-1006

UT code for WoS article

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EID of the result in the Scopus database

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