rte-antares-rpackage / unavailabilityProductionEntsoe

The 'unavailabilityProductionEntsoe' R package

The unavailabilityProductionEntsoe package provides functions to download, analyze and aggregate indisponibility data fram ENTSOE platform.

Installation

Todo!

# Install dependencies

devtools::install_github("rte-antares-rpackage/unavailabilityProductionEntsoe")

Prerequisites

To use this package you must create an account on ENTSOE platform, you will need an acces token.
You can acces to ENTSOE API : https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html

Data download : getDataOutagesProduction

Arguments :

• token : ENTSOE token
• bz : ENTSOE build zone use ENTSOE API
• docType : "A80" for generation unit and "A77" for produciton unit
• docStatus : "A05" for active, "A09" for cancel
• start : start date
• end : end date
• fileToMerge : CSV where data will be save
• by : load data by "day", "week", "month", "year"? Maximum of documents load by request is 200.

Exemple :

library(unavailabilityProductionEntsoe)
token <- "My-token"

#NL
getDataOutagesProduction(token = token, bz = "10YNL----------L", docType = "A80",
   start = "2018-01-01", end = "2018-02-28", fileToMerge = "NLindispo.csv")

Data visualization : runIndispoApp

After use of getDataOutagesProduction, you have save data in a CSV file. You can visualize data with :

 runIndispoApp("NLindispo.csv")

Make time series : giveTS

Arguments :

After use of getDataOutagesProduction, you have save data in a CSV file. You can create time series data with giveTS.

• path : CSV file load with getDataOutagesProduction*
• outFile : new CSV file (output)
• minDate : Date for time series begin
• maxDate : Date for time series end
• overlappingvalues : operation for overlap, can be "sum" or "min".

Exemple :

  giveTS("NLindispo.csv", outFile = "NLindispoTS.csv")

Aggregate time series : aggregateIndispo

Arguments :

• path : CSV file product by giveTS
• aggregatedCol : column to aggregate, can be : "date", "hour", "month", "year", "productionType" can also be a vector (c("month", "year"))
• colDcast : render result by columns : see exemple

Exemple :

 aggregateIndispo("NLindispoTS.csv", "ag1.csv", c("date", "hour", "productionType"))
 aggregateIndispo("NLindispoTS.csv", "ag2.csv", c("date", "hour", "productionType"), colDcast = "productionType")