Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland

In this study, measure-correlate-predict (MCP) algorithms - Simple Linear Regression and Variance Ratio Methods - for predicting wind speed were studied. The MCP algorithms were successfully used to predict missing wind speeds at two sites in Jyväskylä and Viitasaari, respectively. These two algorit...

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Main Author: Saengyuenyongpipat, Paitoon
Other Authors: Matemaattis-luonnontieteellinen tiedekunta, Faculty of Sciences, Fysiikan laitos, Department of Physics, University of Jyväskylä, Jyväskylän yliopisto
Format: Master's thesis
Language:eng
Published: 2010
Subjects:
Online Access: https://jyx.jyu.fi/handle/123456789/23245
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author Saengyuenyongpipat, Paitoon
author2 Matemaattis-luonnontieteellinen tiedekunta Faculty of Sciences Fysiikan laitos Department of Physics University of Jyväskylä Jyväskylän yliopisto
author_facet Saengyuenyongpipat, Paitoon Matemaattis-luonnontieteellinen tiedekunta Faculty of Sciences Fysiikan laitos Department of Physics University of Jyväskylä Jyväskylän yliopisto Saengyuenyongpipat, Paitoon Matemaattis-luonnontieteellinen tiedekunta Faculty of Sciences Fysiikan laitos Department of Physics University of Jyväskylä Jyväskylän yliopisto
author_sort Saengyuenyongpipat, Paitoon
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description In this study, measure-correlate-predict (MCP) algorithms - Simple Linear Regression and Variance Ratio Methods - for predicting wind speed were studied. The MCP algorithms were successfully used to predict missing wind speeds at two sites in Jyväskylä and Viitasaari, respectively. These two algorithms used data from one of the site to predict missing wind speed data at the other site. The results obtained using the MCP methods were compared using metrics that showed the characteristics of the predicted data to be unbiased compared to measured data. From the data of this study, we also evaluated wind power density at both sites which categorized the local wind resources as poor since the determined wind power densities were less than 100 W/m2.
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spellingShingle Saengyuenyongpipat, Paitoon Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland Measure-Correlate-Predict (MCP) algorithms wind energy weibull distribution 402 tuulienergia
title Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland
title_full Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland
title_fullStr Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland
title_full_unstemmed Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland
title_short Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland
title_sort demonstrating measure correlate predict algorithms for estimation of wind resources in central finland
title_txtP Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland
topic Measure-Correlate-Predict (MCP) algorithms wind energy weibull distribution 402 tuulienergia
topic_facet 402 Measure-Correlate-Predict (MCP) algorithms tuulienergia weibull distribution wind energy
url https://jyx.jyu.fi/handle/123456789/23245 http://www.urn.fi/URN:NBN:fi:jyu-201004191537
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