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Published November 30, 2022 | Version 1
Dataset Open

Measuring the flexibility achieved by a change of tariff

  • 1. University of Deusto
  • 2. University of Deustoº
  • 3. GoiEner

Description

  • Name: Measuring the flexibility achieved by a change of tariff.
  • Summary: This dataset contains the results of a survey carried out by the Spanish electricity retailer GoiEner to assess the impact that a change of from a "flat rate" tariff towards a "time of use" tariff have. Two files are provided:
    • The results of the survey merged with a summary of the energy consumption of the clients before and after the change of tariff.
    • The questions of the survey.
  • License: CC-BY-SA
  • Acknowledge: These data have been collected in the framework of the WHY project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 891943.
  • Disclaimer: The sole responsibility for the content of this publication lies with the authors. It does not necessarily reflect the opinion of the Executive Agency for Small and Medium-sized Enterprises (EASME) or the European Commission (EC). EASME or the EC are not responsible for any use that may be made of the information contained therein.
  • Collection Date:
  • Publication Date: December 1, 2022.
  • DOI: 10.5281/zenodo.7382924
  • Other repositories: None.
  • Author: GoiEner, University of Deusto.
  • Objective of collection: The objective of the data collected is to assess the impact that the change of tariff has on the clients of GoiEner. In particular, the following questions wanted to be answered:
    • How much energy conservation can trigger a change of tariff?
    • How much time flexibility could be trigger with a Time of Use Tariff?
    • What are the main barriers to change the behavoiur?
    • Are there any differences on behaviour depending on the socio-cultural-psycological profile of the consumers?
  • Description: The meaning of each column is described next:
    • Qx_y: Answers to the survey. See the survey file attached (in Spanish) for details.
    • X.z: Answers to question "¿En qué rango de horas se realizan las siguientes acciones en el domicilio?". Sorted from left to right, top to bottom.
    • Idioma: Languaje used to answer the survey.
    • Desea.dar.su.CU: data used to de-anonymize the answers.
    • {P,F,V}{19,20,21}: total energy consumed during the peak, flat and valley period of the day between 6/19 to 5/20 (19), 6/20 to 5/21 (20) and 6/21 to 5/22 (21).
    • T{19,20,21}: total energy consumed between 6/19 to 5/20 (19), 6/20 to 5/21 (20) and 6/21 to 5/22 (21).
    • kpi2_abs:  T20 - T21
    • kpi2_rel: kpi2_abs / T20
    • kpi1_{P,F,V}{19,20,21}:   {P,F,V}{19,20,21} / T{19,20,21}
    • kpi1_{P,F,V}diff: kpi1_{P,F,V}19 - kpi1_{P,F,V}21
    • T20DHS{19,20,21}: Cost of the energy of during the different periods using the last tariff.
    • T20TD{19,20,21}: Cost of the energy of during the different periods using the new tariff.
    • POWER_TARGET: Energy powerty rist indicator (https://powerpoor.eu/sites/default/files/2022-09/POWERPOOR%20D2.2%20POWER%20TARGET%20v1.0.pdf)
    • TotalEnergyBudget: Self assessment of the energy budget of the house in Euros.
    • Invoices20{20,21,22}: Amount of all the invoices for the house during the different periods.
    • min30{in,pre,pst}: Cluster assigned depending on its electric behaviour pre-COVID, during the COVID lockdowns and post COVID lockdowns. See 10.5281/zenodo.7382818 for details.
  • 5 star: ⭐⭐⭐
  • Preprocessing steps: Data integration (from different sources from GoiEner services); data transformation (anonymization, unit conversion, metadata generation).
  • Reuse: This dataset is related to datasets:
    • "A database of features extracted from different electricity load profiles datasets" (DOI 10.5281/zenodo.7382818), where time series feature extraction has been performed.
  • Update policy: There might be a single update in mid-2023 with a repetition of the survey as there have been another change of tariff in Spain.
  • Ethics and legal aspects: The data provided by GoiEner contained values of the CUPS (Meter Point Administration Number), which are personal data. A pre-processing step has been carried out to replace the CUPS by random 64-character hashes.
  • Technical aspects: the survey is provided as a PDF file and the data as a CSV file compressed with zstandard.
  • Other: None.

Files

survey_questions.pdf

Files (191.6 MB)

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md5:19cc7ebab9867e46445c4450faf001b7
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md5:6fc4b46eb7b217e5fa5b07cd09d4ba00
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Additional details

Funding

WHY – Climbing the causality ladder to understand and project the energy demand of the residential sector 891943
European Commission