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Wind Energy
Article . 2015 . Peer-reviewed
License: Wiley TDM
Data sources: Crossref
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Wind Energy
Article . 2016
Data sources: VIRTA
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Wind Energy
Article . 2016
Data sources: VIRTA
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A statistical model for comparing future wind power scenarios with varying geographical distribution of installed generation capacity

Wind power scenarios with varying geographical distribution
Authors: Koivisto, M.; Ekström, J.; Seppänen, J.; Mellin, I.; Millar, Robert; Haarla; L.;

A statistical model for comparing future wind power scenarios with varying geographical distribution of installed generation capacity

Abstract

As installed wind generation capacity increases, understanding the effect of wind power on the electric power system is becoming more important. This paper introduces a statistical model that can be used to estimate the variability in wind generation and assess the risk of wind generation contingencies over a large geographical area. The analysis of the installed wind generation capacities is separated from the analysis of the spatial and temporal dependency structures. This enables the study of different future wind power scenarios with varying generation capacities. The model is built on measured hourly wind generation data from Denmark, Estonia, Finland and Sweden. Three scenarios with different geographical distributions of wind power are compared to show the applicability of the model for power system planning. A method for finding the scenario with the minimum variance of the aggregate wind generation is introduced. As the geographical distribution of wind power can be affected by subsidies and other incentives, the presented results can have policy implications. Copyright © 2015 John Wiley & Sons, Ltd.

Related Organizations
Keywords

ta213, power system planning, Gaussian copula, ta111, generalized Pareto distribution, vector autoregressive model, wind power, Monte Carlo simulation

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    popularity
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    Top 10%
    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Top 10%
gold