key: cord-0045097-fs6srtgj
authors: Cama-Pinto, Dora; Martínez-Lao, Juan Antonio; Solano-Escorcia, Andres Felipe; Cama-Pinto, Alejandro
title: Forecasted datasets of electric vehicle consumption on the electricity grid of Spain
date: 2020-06-09
journal: Data Brief
DOI: 10.1016/j.dib.2020.105823
sha: abf50c85c22fe08a96b9c79cf8fe442618b9e515
doc_id: 45097
cord_uid: fs6srtgj

The information included in this study were calculated on the basis of data provided by the Spanish electricity grid, for thirteen years between 2007 and 2019. This data includes: the average consumption demand on the Spanish electricity grid at national level, and its availability. Subsequently, the report looks at the number of electric vehicles that could be supported in the years 2020-2023, depending on the consumption demand and availably of the electricity grid for those future years. The data presented in the article refers to the research study: ‘Electric vehicles in Spain: An overview of charging systems’[1] and ‘Analysis of charging stations for electric vehicles in Spain’ [2].

The electrical capacity in kWh of eighteen models of electric vehicles are shown in the table 1. Each of these models ranges between 15.2 -95 kWh, and is on sale in Spain with prices below 85 thousand euros, being the German car BMW i3s (42.2 kWh) a vehicle with average electric capacity according to the mentioned criterion. The Spanish electricity grid provides raw data of samples with frequencies of 10 minutes, openly accessible to the public, on the demand for electricity consumption at the national level [7] . Each of these values is averaged with all the values of the month for a specific time and year and this is what we observe in the data set stored on the Mendeley data website (https://data.mendeley.com) in the Excel spreadsheet file: Resume_Raw_Data.xlsx. Subsequently, the average of each hour of the day per month between 2007 and 2019 is described in Table 2 . To obtain the values of the average monthly electrical availability during 2007-2019 in megawatts, we the following four steps:

1) The average for a specific time in a month between 2007 and 2019 from the file Resume_Raw_Data.xlsx is located the highest consumption value.

2) This highest consumption value is subtracted with all the values of step1 (average of the month between 2007 -2019 for a specific time in a given month) and we obtain the availability every 10 minutes (the sampling frequency of the Spanish electricity network)

3) The lowest value of electricity availability in each hour is averaged over each of the twelve months between 2007 and 2019 for the same time, the result of each value is shown in Table 3 . 

Is applied linear forecasting technique between the years 2007 to 2019 in the file Resume_Raw_Data.xlsx, The mathematical equation for developing the linear forecast is a+bx,

where x and y are the sample means Average(electric-demand) and

Average(year). In the file Resume_Raw_Data.xlsx is visualized the process to obtain the linear forecast.

On the other hand, the maximum value per month, located in every column of the The values in the table 13,14,15,16 were obtained by dividing every data of the tables 9,10,11,12 per 50 kW. Each result determines the number of new EVs that could be recharged using a fast charge in 60minute intervals with a connection power of 50 kW for the forecasted years 2020, 2021, 2022, 2023 respectively. The summary of tables 13,14,15,16 shows the forecast for 2020-2023 in graphs per month for easy reading in the figure 1. 

The first two months of the year 2020 recorded values close to the linear forecast, with an error of less than 4% in January (a maximum of 3.8% in the 23 to 24 hours), and a maximum error of 4.5% in February (in the 18 to 19 hours interval). However, in March 2020, the error rose to 10% due to the decrease in national electricity demand in Spain as a result of the COVID-19, especially in the 7-11 a.m. time slot. The maximum error peaks are highlighted with green color in Table 17 . 

Electric vehicles in Spain: An overview of charging systems (2017) Renewable and Sustainable Energy Reviews

Analysis of charging stations for electric vehicles in Spain

Energetic, economic and environmental viability of off-grid PV-BESS for charging electric vehicles: Case study of Spain

EU road vehicle energy consumption and CO2 emissions by 2050 -Expert-based scenarios (2020) Energy Policy

Wind missing data arrangement using wavelet based techniques for getting maximum likelihood (2019) Energy Conversion and Management

Seasonal wind energy characterization in the Gulf of Mexico (2019) Energies

This work has been supported by the Government of Andalusia through the Project of Excellence "Analysis of electric power quality using smart meters. Optimisation and savings in the production and residential sector in Andalusia (P10-RNM-6349)", the Project for Applied Knowledge "Analysis and monitoring of electrical power quality using low cost smart meters to save energy (P145096)" and the Ibero-American Postgraduate University Association (AUIP).

The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article.