Historical Hourly Information of Four European Wind Farms for Wind Energy Forecasting and Maintenance

For an electric company, having an accurate forecast of the expected electrical production and maintenance from its wind farms is crucial. This information is essential for operating in various existing markets, such as the Iberian Energy Market Operator—Spanish Hub (OMIE in its Spanish acronym), the Portuguese Hub (OMIP in its Spanish acronym), and the Iberian electricity market between the Kingdom of Spain and the Portuguese Republic (MIBEL in its Spanish acronym), among others. The accuracy of these forecasts is vital for estimating the costs and benefits of handling electricity. This article explains the process of creating the complete dataset, which includes the acquisition of the hourly information of four European wind farms as well as a description of the structure and content of the dataset, which amounts to 2 years of hourly information. The wind farms are in three countries: Auvergne-Rhône-Alpes (France), Aragon (Spain), and the Piemonte region (Italy). The dataset was built and validated following the CRISP-DM methodology, ensuring a structured and replicable approach to data processing and preparation. To confirm its reliability, the dataset was tested using a basic predictive model, demonstrating its suitability for wind energy forecasting and maintenance optimization. The dataset presented is available and accessible for improving the forecasting and management of wind farms, especially for the detection of faults and the elaboration of a preventive maintenance plan.

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Data
Published
2025-03-19
DOI
https://doi.org/10.3390/data10030038
Primary Topic
Energy Load and Power Forecasting
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article
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article

Historical Hourly Information of Four European Wind Farms for Wind Energy Forecasting and Maintenance

Javier Sánchez-Soriano, Carlos Quiterio Gómez Muñoz, Pedro Jose Paniagua-Falo
Data
Energy Load and Power Forecasting
article

Historical Hourly Information of Four European Wind Farms for Wind Energy Forecasting and Maintenance

Javier Sánchez-Soriano, Carlos Quiterio Gómez Muñoz, Pedro Jose Paniagua-Falo
article en

Abstract

For an electric company, having an accurate forecast of the expected electrical production and maintenance from its wind farms is crucial. This information is essential for operating in various existing markets, such as the Iberian Energy Market Operator—Spanish Hub (OMIE in its Spanish acronym), the Portuguese Hub (OMIP in its Spanish acronym), and the Iberian electricity market between the Kingdom of Spain and the Portuguese Republic (MIBEL in its Spanish acronym), among others. The accuracy of these forecasts is vital for estimating the costs and benefits of handling electricity. This article explains the process of creating the complete dataset, which includes the acquisition of the hourly information of four European wind farms as well as a description of the structure and content of the dataset, which amounts to 2 years of hourly information. The wind farms are in three countries: Auvergne-Rhône-Alpes (France), Aragon (Spain), and the Piemonte region (Italy). The dataset was built and validated following the CRISP-DM methodology, ensuring a structured and replicable approach to data processing and preparation. To confirm its reliability, the dataset was tested using a basic predictive model, demonstrating its suitability for wind energy forecasting and maintenance optimization. The dataset presented is available and accessible for improving the forecasting and management of wind farms, especially for the detection of faults and the elaboration of a preventive maintenance plan.

DataVol. 10(3)
Universidad Francisco de Vitoria (ES), Universidad Autónoma de Madrid (ES)
Consejería de Sanidad, Comunidad de Madrid
Openalex Percentile: Top 96%
Energy Load and Power Forecasting
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Historical Hourly Information of Four European Wind Farms for Wind Energy Forecasting and Maintenance — Javier Sánchez-Soriano, Carlos Quiterio Gómez Muñoz, et al. · Data (2025) | TGRS Research Map | TGRS