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

  • Koivisto M
  • Ekström J
  • Seppänen J
 et al. 
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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.

Author-supplied keywords

  • Gaussian copula
  • Monte Carlo simulation
  • generalized Pareto distribution
  • power system planning
  • vector autoregressive model
  • wind power

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  • M. Koivisto

  • J. Ekström

  • J. Seppänen

  • I. Mellin

  • J. Millar

  • L. Haarla

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