Are local wind power resources well estimated?
نویسندگان
چکیده
منابع مشابه
Cost of wind energy: comparing distant wind resources to local resources in the midwestern United States.
The best wind sites in the United States are often located far from electricity demand centers and lack transmission access. Local sites that have lower quality wind resources but do not require as much power transmission capacity are an alternative to distant wind resources. In this paper, we explore the trade-offs between developing new wind generation at local sites and installing wind farms...
متن کاملSpatial Distribution of Estimated Wind-Power Royalties in West Texas
Wind-power development in the U.S. occurs primarily on private land, producing royalties for landowners through private contracts with wind-farm operators. Texas, the U.S. leader in wind-power production with well-documented support for wind power, has virtually all of its ~12 GW of wind capacity sited on private lands. Determining the spatial distribution of royalty payments from wind energy i...
متن کاملAre global wind power resource estimates overstated?
Estimates of the global wind power resource over land range from 56 to 400 TW. Most estimates have implicitly assumed that extraction of wind energy does not alter large-scale winds enough to significantly limit wind power production. Estimates that ignore the effect of wind turbine drag on local winds have assumed that wind power production of 2–4 W m−2 can be sustained over large areas. New r...
متن کاملActive multiple kernel learning of wind power resources
Wind power resources in mountainous regions are conditioned on a vast variety of factors influencing air flow. Complex topography causes various phenomena such as localised thermal winds, acceleration due to tunneling and Foehn winds interfering at a range of spatial scales and varying in time due to weather seasonality. It increases the dimensionality of parameter space and adds additional com...
متن کاملDiffusion Maps and Local Models for Wind Power Prediction
In this work we will apply Diffusion Maps (DM), a recent technique for dimensionality reduction and clustering, to build local models for wind energy forecasting. We will compare ridge regression models for K–means clusters obtained over DM features, against the models obtained for clusters constructed over the original meteorological data or principal components, and also against a global mode...
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ژورنال
عنوان ژورنال: Environmental Research Letters
سال: 2013
ISSN: 1748-9326
DOI: 10.1088/1748-9326/8/1/011005