• Corpus ID: 238857174

Trading Data for Wind Power Forecasting: A Regression Market with Lasso Regularization

@article{Han2021TradingDF,
  title={Trading Data for Wind Power Forecasting: A Regression Market with Lasso Regularization},
  author={Liyang Han and Pierre Pinson and Jalal Kazempour},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.07432}
}
  • Liyang Han, P. Pinson, J. Kazempour
  • Published 14 October 2021
  • Computer Science, Mathematics, Engineering
  • ArXiv
This paper proposes a regression market for wind agents to monetize data traded among themselves for wind power forecasting. Existing literature on data markets often treats data disclosure as a binary choice or modulates the data quality based on the mismatch between the offer and bid prices. As a result, the market disadvantages either the data sellers due to the overestimation of their willingness to disclose data, or the data buyers due to the lack of useful data being provided. Our… 

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