Optimizing wind farm locations to reduce variability and increase generation

@article{Lowery2014OptimizingWF,
  title={Optimizing wind farm locations to reduce variability and increase generation},
  author={Colm Lowery and Mark J. O'Malley},
  journal={2014 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)},
  year={2014},
  pages={1-7}
}
With the drive towards increased wind penetration, the nature of power system operation is changing. In particular, the uncertainty of wind generation becomes exacerbated by the nature of the deregulated market. Rather than wind farm location being selected to compliment existing wind generation, the planning process for wind farms reward maximizing the generation of each wind farm. This paper presents and demonstrates a methodology for estimating and comparing wind generation portfolios whose… CONTINUE READING

Citations

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Optimised Geographical Allocation of Wind Energy Capacity using a Mean-Variance Portfolio Algorithm for Clustered and Un-clustered Profiles

  • 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
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Short-Term Ensemble NWP Wind Speed Forecasts using Mean-Variance Portfolio Optimization and Neural Networks

  • 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
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