Configuring scenarios¶

A scenario-based approach is incorporated in the OpenTUMFlex design. The term scenarios in OpenTUMflex means cases or examples. A scenario refers to the device configurations installed in a household. For example, a scenario can refer to a household with PV, BSS and EV while a different household with just PV and HP is considered as another scenario.

You can create scenarios of your own or modify/use the existing scenarios. The file inside OpenTUMflex->Scenario->scenario.py serves as the main file to decide which scenarios are available.

Default scenarios¶

Once you have successfully installed and test run your OpenTUMFle, then scenario_apartment is executed by default. You can choose to change your scenario by replacing the desired keyword in line 12 in example.py. To give an idea, we have already created 8 sample scenarios inside scenario.py.

Following scenarios are created based on possible combination of devices installed at any prosumers premises.

Scenario	Devices
`scenario_hp`	HP and boiler
`scenario_pv`	PV and boiler
`scenario_bat`	BSS and boiler
`scenario_ev`	EV and boiler
`scenario_simple_house`	PV, BSS, heat storage and boiler
`scenario_residential_house`	PV, BSS, heat storage and boiler
`scenario_mini_apartment`	PV, BSS, heat storage, boiler, HP and EV
`scenario_apartment`	PV, BSS, heat storage, boiler, CHP, HP and EV

Scenario from file

OpenTUMFlex allows to you to directly create a scenario from your input file based on the devices included. To allow this use scenario_fromfile as keyword.

Creating scenarios¶

OpenTUMFlex allows two ways to create a new scenario.

Using .xlsx/.csv input file

Inside the input folder, we have added an example .xlsx file to understand the input format.
Modify the excel cells based on your scenario.
Add zeros to parameters in case the device is not available in your scenario.
Point the input directory variable input_file=Path to the input .xlsx/.csv
Use opentumflex.scenario_fromfile as the argument while calling run_scenario function.
To speed up the total time, we have the option to create/use CSV. See x.x.
Remember this method uses both the input file sheets namely properties and time_series.
This method is useful if you wish to run OpenTUMflex for a single case study.

Using functions

Create a new function inside OpenTUMflex->Scenario->scenario.py.
As an example, let’s say the function name is scenario_happyhouse.
Use opentumflex.scenario_happyhouse as the argument while calling the run_scenario function.
Remember this method also uses the input file but only the time_series sheet.
Make changes to the .xlsx/.csv input file to amend the input time series data.
This method is useful during analysis, e.g. modify device parameters iteratively.

File formats¶

Input file formats

OpenTUMflex accepts two different file formats (.xlsx/.csv) as input.
Example input file is available inside the input folder.
CSV files are generally preferred as they reduce the overall optimization time.
XLSX file can be also used for better readability and practice.
The model has an inbuilt option to convert any .xlsx file to .csv files.

Warning

Do not change the structure of the .csv/.xlsx files. OpenTUMFlex can read the inputs only using the defined sheet settings. Sample .csv/.xlsx formats are available in the input folder.

Converting .xlsx files to .csv

To convert your .xlsx file to .csv format, run example.py once with .xlsx file as your input and make sure to assign convert_input_tocsv= True. After the execution a CSV file is automatically generated and saved into the input folder. For the subsequent runs you may use the CSV format and disable convert_input_tocsv = False.

Output file format

OpenTUMFlex can generate a variety of plots such as optimal operation, SOC, flexibility, etc.
These images can be stored as JPG files in the output folder.
X.X discusses the arguments to save the output images.
Flexibility offers of each device in suitable formats can be generated as .csv files
Formatted Output files can be used in FlexMarket trading - e.g. ALF/ COMAX platforms.
X.X discusses the arguments to save the output files in defined format.

I/O structure¶

Input file structure

The input file consists of two parts which are namely the device properties and the forecasted time series values. In XLSX format, it is implemented as two sheets namely properties and time_series. In the CSV format, the time series data is concatenated with the device properties and are seperated by ;.

The following parameters are used for defining device properties.

Device	Parameters
PV	Peak power
BSS	Charging/discharging Power (Min & Max), Initial SOC, Capacity, Efficiency
EV	Charging/discharging Power (Min & Max), Initial & End SOC, Capacity, Efficiency
HP	Min & Max Power utilized
CHP	Min & Max Power utilized
HS	Charging/discharging Power (Min & Max), Initial SOC, Capacity, Efficiency, Self discharge

The following parameters are used for defining the time series forecast data.

Forecast data	Units
Temperature	°C
PV power	kW
EV availability data	Binary
Heat load	kW
Electrical load	kW
Electricity import price	€/kWh
Electricity export price	€/kWh
Gas price	€/kWh

Output file structure

The output of the OpenTUMFlex model is the flexibility table that can be used for trading. The flexibility table consists of the scheduled operation along with the possible flexibility service that can be offered in terms of power, energy and price.

The flexibility energy refers to the amount of negative or positive flexibility power that can last over a specific period (timesteps). The flexibility price is the cost that prosumer bids for providing a specific flexibility service. An excerpt from a sample table is provided below and uses COMAX flexibilty platform based output format.

Time	Sch_P	Neg_P	Pos_P	Neg_E	Pos_E	Neg_Pr	Pos_Pr
2019-12-18 01:30	0.6615	-3.661	2.338	-0.915	1.169	-0.298	0.279
2019-12-18 01:45	0.5808	-3.580	2.419	-0.895	0.604	-0.298	0.279
2019-12-18 02:00	0.0000	-3.000	3.000	-3.000	0.750	-0.287	0.279
2019-12-18 02:15	0.0000	-3.000	3.000	-3.000	0.750	-0.287	0.279