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Oklahoma State University (2012)

Influences of Geographic Factors on the Complementary Nature of Wind Power and Insolation

Li, Weiping

Titre : Influences of Geographic Factors on the Complementary Nature of Wind Power and Insolation

Auteur : Li, Weiping

Université de soutenance : Oklahoma State University

Grade : Doctor of Philosophy (PhD) 2012

Résumé
Scope and Method of Study : The major objective of this study is to investigate the spatial variation of the complementary nature of wind power and solar radiation (CWS), and how geographic factors impact this nature. Quantification approaches, spatial analysis, especially local geographically weighted regression (GWR) methodology are employed to conduct this study. Local geographic factors from micro to mesoscale are associated with the CWS. Their relationships are further examined through statistics, principal components analysis, and GWR modeling. Oklahoma with typical terrain variations and high-resolution Mesonet data is used as an exemplary case for this study. Because of time limitation, this study is basically preliminary. The variation of the complementary nature in a wider spatial and temporal scale, and many theoretical and practical issues related with this topic are not explored by this study. Findings and Conclusions : Through applying quantification approach and local spatial analysis methods on the exemplary case of Oklahoma, this study found that there exist complementarity of wind power and solar radiation (CWS) in different levels during different temporal span at different places. In Oklahoma, the average annual level of CWS can range from 0.28 to 0.62 where 1 means the highest. Geographic factors like moisture, landscape focusing on slope/forest coverage, landscape focusing on curvature, landscape focusing on barren and residential land percentage, and landscape focusing on aspect/relative elevation are found significantly related with CWS. In global model, except that the dimension of landscape focusing on barren and residential land percentage is found negatively impacting the CWS, all other three dimensions are positively affecting the CWS. However, in local GWR model, the sign of their relations with the CWS vary with space, and may hold opposite signs in different regions. Through local GWR modeling, it is also found that only the influences of the moisture dimension on the CWS indicate significant spatial variation. By examining the statistics of local GWR models and corresponding global models, it is found local models did not outperform global models in most cases. Therefore there is probably a global model to estimate the level of CWS based on local or regional geographic factors.

Mots clés : Complementarity, Geographic Statistics, GWR, Solar Energy, Spatial Analysis, Wind Power

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Page publiée le 26 novembre 2014, mise à jour le 8 septembre 2017