Wind Speed's Impact on Spanish Power Prices
A Study of Market Efficiency
By [source]
About this dataset
This dataset provides a comprehensive analysis of the influence of wind speeds on short-term electricity prices in the Spanish electricity market, OMIE. It includes information on average, minimum and maximum daily power prices in euros per megawatt hour (€/MWh) along with corresponding data from observational points about wind speed and strong gusts in kilometres per hour (km/h).
By exploring the interactions between weather patterns and energy markets, this dataset is a valuable tool for energy stakeholders looking to forecast and manage their prices more effectively. It’s also an important resource for scientists, weather agencies and environmental regulators who need to get a handle on how changing wind patterns can impact pricing in the short term. Finally, this data is ideal for educational use as well – providing an insightful overview of how external factors can influence power costs
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How to use the dataset
This dataset is useful to identify the influence of wind speed observations on the power prices in the Spanish electricity market, OMIE. By understanding this relationship, stakeholders can develop strategies to forecast, manage and optimize energy production and consumption.
To make use of this dataset one should begin by exploring the data with visualizations and summary statistics. This will provide an overview of the average daily prices in euros per megawatt hour (€/MWh) as well as associated temperatures obtained by a series of wind data observation points in kilometres per hour (km/h). Comparing these variables will allow for analysis into their correlations and any seasonal fluctuations present. Additionally, further exploration can be made by plotting multiple variables against each other such as maximum power prices and percentage of maximum wind speeds achieved over various timeframes.
Once the individual components are better understood, more comprehensive assessment can be conducted including linear regression models to evaluate interaction between independent variablen like hourly temperature observations and dependent variables like price fluctuations due to variability in demand or supply availability within given hours or days etc. With this knowledge refined analysis can be done not only with current data but future predictions from driving forces within market trends etc along with relevant external factors such as weather patterns etc too if needed could also be studied using correlation or causality studies using advanced modelling techniques if required
Research Ideas
- Developing pricing models and strategies in the energy market by analyzing the correlation between wind speeds and power prices across different time periods compared to various influencing factors such as supply, demand, weather conditions etc.
- Utilizing this data to develop concepts and strategies for forecasting electricity prices with much higher accuracy than traditional methods .
- Exploring the impacts of wind farm construction on the voltage stability and long-term price trends in regional electric grids by studying how new wind farms affect the regional power mix mix and corresponding supply/demand curves over time
Acknowledgements
If you use this dataset in your research, please credit the original authors.
Data Source
License
License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
Columns
File: wind_vs_price.csv
| Column name |
Description |
| fecha |
Date of the observation. (Date) |
| MIN(dp.precio) |
Minimum daily power price in euros per megawatt hour (€/MWh). (Numeric) |
| AVG(dp.precio) |
Average daily power price in euros per megawatt hour (€/MWh). (Numeric) |
| MAX(dp.precio) |
Maximum daily power price in euros per megawatt hour (€/MWh). (Numeric) |
| AVG(wd.vel_km_h) |
Average wind speed in kilometres per hour (km/h). (Numeric) |
| MAX(wd.racha_max_km_h) |
Maximum wind speed in kilometres per hour (km/h). (Numeric) |
File: da_price.csv
| Column name |
Description |
| fecha |
Date of the observation. (Date) |
| datetime_utc |
Date and time of the observation in UTC. (DateTime) |
| sistema |
System of the observation. (String) |
| hora |
Hour of the observation. (Integer) |
| bandera |
Flag of the observation. (String) |
| precio |
Price of the observation. (Float) |
| fecha_actualizacion |
Date of the last update of the observation. (Date) |
Acknowledgements
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .