demandlib Documentation

Transcription

1 demandlib Documentation Release beta Uwe Krien, oemof developing group November 30, 2016

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3 Contents 1 Getting started Introduction Current Release Developing Version Example What s New v0.1.2 () v0.1.1 (November 30, 2016) v0.1 (October 04, 2016) Model Description BDEW Furter Profiles demandlib package Submodules demandlib.bdew module demandlib.particular_profiles module demandlib.tools module Module contents Indices and tables 13 Python Module Index 15 i

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5 demandlib Documentation, Release beta Contents: Contents 1

6 demandlib Documentation, Release beta 2 Contents

7 CHAPTER 1 Getting started The demandlib is part of the oemof group but works as a standalone application. Table of contents Introduction Current Release Developing Version Example 1.1 Introduction With the demandlib you can create power and heat profiles for various sectors by scaling them to your desired demand. Additionally you can specify a year so that holidays are considered respectively. 1.2 Current Release Current release of demandlib is v0.1.1 Install it via pip sudo pip3 install demandlib 1.3 Developing Version Documentation Read the latest documentation at Readthedocs.org Installation Clone the demandlib from github. 3

8 demandlib Documentation, Release beta git clone If the project is cloned you can install it using pip3 with the -e flag. sudo pip3 install -e <path/to/the/demandlib/root/dir> Developing the demandlib As the demandlib is part of the oemof developer group we use the same developer rules: If you have push rights clone this repository to your local system. git clone If you want to contribute, fork the project at github, clone your personal fork to your system and send a pull request. 1.4 Example Take a look on the examples to get usage of demandlib. We provide two examples. One for the heat sector, executable by calling demandlib_heat_example. The second example show how to create demand time-series for the power. Execute this example by calling demandlib_power_example. Both exemaples are callable from anywhere in the command-line. 4 Chapter 1. Getting started

9 CHAPTER 2 What s New These are new features and improvements of note in each release Releases v0.1.2 () v0.1.1 (November 30, 2016) v0.1 (October 04, 2016) 2.1 v0.1.2 () New features Documentation Testing Bug fixes Other changes Contributors 2.2 v0.1.1 (November 30, 2016) New features Examples callable by command-line script Bug fixes Path specs when installed via pip 5

10 demandlib Documentation, Release beta Other changes Fix versioning Contributors Guido Pleßmann Uwe Krien 2.3 v0.1 (October 04, 2016) New features Implementation of BDEW synthetic load profiles Synthetic load profiles for heating sector Self-made industry demand profile similar to BDEW profiles Contributors Uwe Krien Caroline Möller Birgit Schachler Guido Plessmann 6 Chapter 2. What s New

11 CHAPTER 3 Model Description 3.1 BDEW Using the demandlib you can create heat and electrical profiles by scaling the BDEW profiles to your desired annual demand. The BDEW profiles are the standard load profiles from BDEW... (heat?) Heat Profiles Heat profiles Electrical Profiles The electrical profiles are the standard load profiles from BDEW. You can choose from H0, G0...G6 and L0...L3 (?) by defining an annual demand for any of these options. 3.2 Furter Profiles We implemented further profiles (one until now) to represent further demand sectors which are not covered by the BDEW load profiles Industrial Electrical Profile The industrial electrical profile uses a step function. 7

12 demandlib Documentation, Release beta 8 Chapter 3. Model Description

13 CHAPTER 4 demandlib package 4.1 Submodules 4.2 demandlib.bdew module Implementation of the bdew heat load profiles class demandlib.bdew.elecslp(year, seasons=none, holidays=none) Bases: object Generate electrical standardized load profiles based on the BDEW method. datapath string Path to the csv files containing the load profile data. date_time_index pandas.datetimeindex Time range for and frequency for the profile. Parameters year (integer) Year of the demand series. Parameters (Optional) seasons (dictionary) Describing the time ranges for summer, winter and transition periods. holidays (dictionary or list) The keys of the dictionary or the items of the list should be datetime objects of the days that are holidays. all_load_profiles(time_df, holidays=none) create_bdew_load_profiles(dt_index, slp_types, holidays=none) Calculates the hourly electricity load profile in MWh/h of a region. get_profile(ann_el_demand_per_sector) Get the profiles for the given annual demand Parameters ann_el_demand_per_sector (dictionary) Key: sector, value: annual value 9

14 demandlib Documentation, Release beta Returns pandas.dataframe Return type Table with all profiles class demandlib.bdew.heatbuilding(df_index, **kwargs) Bases: object Parameters year (int) year or which the profile is created datapath string path to the bdew basic data files (csv) temperature pandas.series Series containing hourly temperature data annual_heat_demand float annual heat demand of building in kwh building_class int class of building according to bdew classification possible numbers are: 1-11 shlp_type string type of standardized heat load profile according to bdew possible types are: GMF, GPD, GHD, GWA, GGB, EFH, GKO, MFH, GBD, GBA, GMK, GBH, GGA, GHA wind_class int wind classification for building location (0=not windy or 1=windy) ww_incl boolean decider whether warm water load is included in the heat load profile get_bdew_profile() Calculation of the hourly heat demand using the bdew-equations get_sf_values(filename= shlp_hour_factors.csv ) Determine the h-values Parameters filename (string) name of file where sigmoid factors are stored get_sigmoid_parameters(filename= shlp_sigmoid_factors.csv ) Retrieve the sigmoid parameters from csv-files Parameters filename (string) name of file where sigmoid factors are stored get_temperature_interval() Appoints the corresponding temperature interval to each temperature in the temperature vector. get_weekday_parameters(filename= shlp_weekday_factors.csv ) Retrieve the weekday parameter from csv-file Parameters filename (string) name of file where sigmoid factors are stored 10 Chapter 4. demandlib package

15 demandlib Documentation, Release beta weighted_temperature(how= geometric_series ) A new temperature vector is generated containing a multi-day average temperature as needed in the load profile function. Parameters how (string) string which type to return ( geometric_series or mean ) Notes Equation for the mathematical series of the average tempaerature 1 : T = T D T D T D T D with T D = Average temperature on the present day T D i = Average temperature on the day - i References 4.3 demandlib.particular_profiles module Implementation of the bdew standard load profiles for electric power. class demandlib.particular_profiles.industrialloadprofile(dt_index, holidays=none) Bases: object Generate an industrial heat or electric load profile. simple_profile(annual_demand, **kwargs) Create industrial load profile Parameters annual_demand (float) Total demand. Other Parameters am (datetime.time) beginning of workday pm (datetime.time) end of workday week (list) list of weekdays weekend (list) list of weekend days profile_factors (dictionary) dictionary with scaling factors for night and day of weekdays and weekend days 4.4 demandlib.tools module Tools needed by the main classes demandlib.tools.add_weekdays2df(time_df, holidays=none, holiday_is_sunday=false) Giving back a DataFrame containing weekdays and optionally holidays for the given year. Parameters time_df (pandas DataFrame) DataFrame to which the weekdays should be added Parameters (Optional) 1 BDEW, BDEW Documentation for heat profiles demandlib.particular_profiles module 11

16 demandlib Documentation, Release beta holidays (array with information for every hour of the year, if holiday or) not (0: holiday, 1: no holiday) holiday_is_sunday (boolean) If set to True, all holidays (0) will be set to sundays (7). Returns pandas.dataframe Return type DataFrame with weekdays Notes Using Pandas > Module contents 12 Chapter 4. demandlib package

17 CHAPTER 5 Indices and tables genindex modindex search 13

18 demandlib Documentation, Release beta 14 Chapter 5. Indices and tables

19 Python Module Index d demandlib, 12 demandlib.bdew, 9 demandlib.particular_profiles, 11 demandlib.tools, 11 15

20 demandlib Documentation, Release beta 16 Python Module Index

21 Index A add_weekdays2df() (in module demandlib.tools), 11 all_load_profiles() (demandlib.bdew.elecslp method), 9 annual_heat_demand (demandlib.bdew.heatbuilding attribute), 10 B building_class (demandlib.bdew.heatbuilding attribute), 10 C create_bdew_load_profiles() method), 9 (demandlib.bdew.elecslp D datapath (demandlib.bdew.elecslp attribute), 9 datapath (demandlib.bdew.heatbuilding attribute), 10 date_time_index (demandlib.bdew.elecslp attribute), 9 demandlib (module), 12 demandlib.bdew (module), 9 demandlib.particular_profiles (module), 11 demandlib.tools (module), 11 E ElecSlp (class in demandlib.bdew), 9 G get_bdew_profile() (demandlib.bdew.heatbuilding method), 10 get_profile() (demandlib.bdew.elecslp method), 9 get_sf_values() (demandlib.bdew.heatbuilding method), 10 get_sigmoid_parameters() (demandlib.bdew.heatbuilding method), 10 get_temperature_interval() (demandlib.bdew.heatbuilding method), 10 get_weekday_parameters() (demandlib.bdew.heatbuilding method), 10 H HeatBuilding (class in demandlib.bdew), 10 I IndustrialLoadProfile (class in demandlib.particular_profiles), 11 S shlp_type (demandlib.bdew.heatbuilding attribute), 10 simple_profile() (demandlib.particular_profiles.industrialloadprofile method), 11 T temperature (demandlib.bdew.heatbuilding attribute), 10 W weighted_temperature() (demandlib.bdew.heatbuilding method), 10 wind_class (demandlib.bdew.heatbuilding attribute), 10 ww_incl (demandlib.bdew.heatbuilding attribute), 10 17