Data for all Challenges

Data Smart Charging Hackathon: Unleash the power!

This document summarizes the data that is available to work with. Some data is available via an internet link others accessible via excel files. For each data set there is a short description. Please ask an expert or someone of the organization for additional information. 

 

OCPI Interface 

Here comes the sun challenge. Document (pdf) concerning the OCPI 0.4 interface. Used for the sending charging profiles to the charging stations.

This is what you need:

Download: 

OCPI-Draftv4.pdf

OCPI-examples.docx

EVIDs.docx

Icarus local energy flows

Description:

iCarus predicts local energy flows. Both generated energy by sun or wind, but also energy consumption, for example by electric cars.

This data is available per municipality, per province, and for the Netherlands as a whole. For this hackathon, only the data for municipalities from the province of Noord-Holland is available at municipal level.

Historical and predicted energy flows are available via an API (and, if internet connection is not working properly, as a backup via a file).

This is what you need

The API is protected with a username + password: icarusaccapi + By4rInyr

https://acc-data.icarus.energy/api/forecast?key=Nederland&fromDate=2018-02-28

https://acc-data.icarus.energy/api/forecast?key=Provincies&fromDate=2018-02-28

https://acc-data.icarus.energy/api/forecast?key=Provincie_Noord-Holland&fromDate=2018-02-28

Download API-iCarus: Containing:

  • Nederland.json
  • Provincie_Noord-Holland.json
  • Provincies.json 

Daily Profiles

Description:

Charging behavior of EV’s bases on charging data for public, workplace and private charges whereby a distinction is made between weekdays and weekend days.

Per sheet you can find the following columns;

·         Time of day (k)

·         Proportion of sessions started in k.

What you need:

Download: Daily_profiles.xlsx

 

Distribution energy duration

 

Description:

Contains distribution tables for connection time and energy volumes per category of chargers.  

Based dataset 1 & dataset 2 one should be able to simulate charging data.

The dataset includes an overview of 1000 random transactions from public charging stations. The following data will be provided under this agreement:

 

Dataset 1: Transactions data

Transaction ID
The unique transaction code.

ChargePoint ID
The unique code of a charging station.

Connector ID
Many charging stations have two connections (two sockets for charge plugs) and this indicates what connector was used for the transactions.

Started
The moment the transaction was started (logged in locale time zone).

Ended
The moment the plug was disconnected and the transaction was stopped.

MeterStart
The meter value (Wh) at the start of a transaction.

MeterStop
The meter value (Wh) at the end of a transaction.

ConnectedTime

Time difference between the start and end of a transaction. 

 

Dataset 2: Meterreadings

 

Transaction ID
The unique transaction code.

ChargePoint ID
The unique code of a charging station.

Connector ID
Many charging stations have two connections (two sockets for charge plugs) and this indicates what connector was used for the transactions.

UTCTime
Date and time stamp of the meter reading in UTC time zone.

LocaleTime15m
Date and time (rounded to the nearest 15 min.) stamp of the meter reading in locale time zone.

Collectedvalue
Meter readings in kWh with 15 minutes intervals.

EnergyInterval

Total energy (kWh) transfer between two consecutive meter readings.

AveragePower
Average power in kW between two consecutive meter readings. 

What you need:

 

Download: Distribution_energy_duration.xlsx

 

Charging profile

Description:

Contains 1000 random charging profiles that belong to full electric vehicles at public chargers. See also attached a description of this data.

What you need:

Download: Charging_profiles.xlsx

 

Transformer profile

Contains mean, minimum, and maximum power demand for a typical 400 kVA medium voltage substation. You can find weekly profiles per season.

What you need:

Confidential, ask for permission of this dataset at the organization.

 

Dutch meteorological data  (KNMI)

Dutch weather forecast model: http://data.knmi.nl 

Meteosat, downloading with OpenGCservices (WMS/WCS) global and diffuse solar radiation: http://msgcpp.knmi.nl

Cabauw BSRN, global and diffuse solar radiation data: http://projects.knmi.nl/cabauw/bsrn/quicklooks/BSRN_dy.php?csrc=bsrn&day=2018-03-07

 

 

Data Dutch Grid Operators

https://www.liander.nl/over-liander/innovatie/open-data/data

https://www.stedin.net/zakelijk/open-data

https://www.enexis.nl/over-enexis/open-data

 

Other relevant data

Data links: 

Climate monitor; logs several demographic information concerning energy and environment. Datalog of company cars per municipality.

https://klimaatmonitor.databank.nl/Jive

Tennet TSO data; several files of historic electricity prices, electricity balances, power availability

http://www.tennet.org/bedrijfsvoering/ExporteerData.aspx

Multiple energy data sets and information on energy techniques and innovation.

http://en-tran-ce.org/newsletter-renewable-energy-in-the-netherlands/

Data about performances of multiple electric vehicles that are available in the market.

https://ev-database.nl/cheatsheet/actieradius-elektrische-auto

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