README.md

In wagnertimo/rmarketcrawlR: Crawling operating reserve data (15min calls, auction prices, 4sec needs)

rmarketcrawlR: crawling data of the german energy reserve market

Goal

This R package provides functions to crawl the german operating reserve market of the platform https://www.regelleistung.net. It is build as part of my master thesis to analyze the call probability of secodary reserve power depending on the offered work price. The aim is to predict such call probabilities, for improving existing optimization algorithms which relay on assumptions and are not very accurate. For further information please get in contact or follow my (blog)[https://wagnertimo.github.io].

Get Started

Installing

When installing this package you should at least use the R version 3.3.0 (2016-05-03). For the library dependecies see the section below. You can easily install this R package by using the install_github() function from the devtools package:

library(devtools)
install_github("wagnertimo/rmarketcrawlR")

Library dependencies

Before using this R package, please check that you have installed the following R packages. Normally, with the installation of the package those dependencies will also be installed. If not, you have to do it manually.

• httr
• xml2
• XML
• zoo
• lubridate
• timeDate
• dplyr
• tidyr
• magrittr
• data.table
• doParallel
• foreach
• logging

Usage

Get operating reserve power data

There are three main functions which allows you to crawl operating reserve calls, needs and auction results of the german operating reserve market. The operating reserve power data (specified by the parameter rl) is provided by the transperant website (https://www.regelleistung.net) of the four energy system providers (specified by the parameter uenb):

• getReserveCalls(startDate, endDate, uenb, rl): It retrieves the 15min operating reserve calls for several products and providers (source: https://www.regelleistung.net/ext/data/). It is important that you do not exceed the time range over several years including the daylight saving date (last sunday of october). Since then the addTimezone() function creates false data. This user inconvenience is not yet corrected. Checkout documentation for further information ?getReserveCalls.

• getReserveAuctions(startDate, endDate, rl): It retrieves the operating reserve auction results (anonymous order list of energy providers; MOL) for a specific product and time period (source: https://www.regelleistung.net/ext/tender/). The data gets formatted. Checkout documentation for further information ?getReserveAuctions.

• getReserveNeeds(startDate, endDate): It retrieves the operating reserve needs for a specific time frame of the Netzregelverbund (NRV) based on a 4 sec resolution (source: https://www.transnetbw.de/de/strommarkt/systemdienstleistungen/regelenergie-bedarf-und-abruf). It is important that you do not exceed the time range over several years including the daylight saving date (last sunday of october). Since then the addTimezone() function creates false data. This user inconvenience is not yet corrected. Checkout documentation for further information ?getReserveNeeds.

It is important to mention that the function getReserveNeeds() will cause an error if in the main project path (working directory) other .csv files are located. Such files should be moved to another folder (e.g. data folder).

Below you will find an example code snippet. It is shown how to crawl the secodary reserve power data. The auctions data is weekly based from monday till sunday. The getReserveAuctions() functions takes care of mapping the input dates to the right weekly beginning and ending. It is also important that you have to set the logging state in the beginning. Till now, there is no default value for it. Avoiding to set the log status will break the functions. Every main function will trigger a log file to be written in the workspace directory (with execution time in its name).

# Activate the package in the workspace
library(rmarketcrawlR)

# You have to set logging to TRUE or FALSE if you want logs printed out and written in a file (Good for Debugging)
# No default yet. Will break if not set.
setLogging(TRUE)

# Get sample data for operating needs, calls and auctions of secondary reserve power from the Netzregelverbund
needs = getReserveNeeds('01.01.2016', '10.01.2016')
calls = getReserveCalls('01.01.2016', '10.01.2016', '6', 'SRL') # 6 == Netzregelverbund, SRL == secodary reserve power
auctions = getReserveAuctions('01.01.2016', '10.01.2016', '2') # 2 == secondary reserve power

Notes

Data for operating reserve calls are available since 2011-06-27 at https://www.regelleistung.net/ext/data/. Data for operating reserve needs (4sec data) are available since July 2010 at https://www.transnetbw.de/de/strommarkt/systemdienstleistungen/.

There are missing values and outliers. Outliers were identified for the operative reserve needs in 2011 and 2012. Those oultliers are characterized by continuous zero values over a longer period of observations. There are also missing values for operative reserve needs in 2012 (observations are marked with "NaN") and for operative reserve calls in 2011, 2012 and 2013 (negative and positive power of the Netzregelverbund).

Version v04 - 16.06.2017

wagnertimo/rmarketcrawlR documentation built on May 3, 2019, 7:37 p.m.