• Corpus ID: 238857174

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

  title={Trading Data for Wind Power Forecasting: A Regression Market with Lasso Regularization},
  author={Liyang Han and Pierre Pinson and Jalal Kazempour},
  • 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… 

Figures from this paper


Towards Data Markets in Renewable Energy Forecasting
Geographically distributed wind turbines, photovoltaic panels and sensors (e.g., pyranometers) produce large volumes of data that can be used to improve renewable energy sources (RES) forecasting
Introducing distributed learning approaches in wind power forecasting
  • P. Pinson
  • Engineering
    2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)
  • 2016
Renewable energy forecasting is now of core interest to both academics, who continuously propose new forecast methodologies, and forecast users for optimal operations and participation in electricity
Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting
A Marketplace for Data: An Algorithmic Solution
This work designs a data marketplace; a robust real-time matching mechanism to efficiently buy and sell training data for Machine Learning tasks and proposes a mathematical model for a two-sided data market and formally defines the key associated challenges.
LASSO vector autoregression structures for very short-term wind power forecasting
The deployment of smart grids and renewable energy dispatch centers motivates the development of forecasting techniques that take advantage of near real-time measurements collected from
Too Much Data: Prices and Inefficiencies in Data Markets
When a user shares her data with an online platform, she typically reveals relevant information about other users. We model a data market in the presence of this type of externality in a setup where
Markets for Information: An Introduction
We survey a recent and growing literature on markets for information. We offer a comprehensive view of information markets through an integrated model of consumers, information intermediaries, and
A Spatio-Temporal Analysis Approach for Short-Term Forecast of Wind Farm Generation
Numerical test results demonstrate the improved performance of the Markov chains developed by spatio-temporal analysis over existing approaches, including persistence forecasts and high-order autoregressive model-based point forecasts.
Data and the Aggregate Economy
While the data economy has changed the way people shop and businesses operate, it has only just begun to permeate economists’ thinking about aggregate economic phenomena. In the early twentieth
The Value of Personal Information in Online Markets with Endogenous Privacy
It is shown that the optimal selling strategy for the owner of consumer data consists in dealing exclusively with one firm in order to create maximal competition between the winner and the loser of data, and policy makers should concentrate their attention on exclusivity deals rather than making it easier for consumers to protect their privacy.