Application¶

The user interface can be used to

create energy system models,
perform optimization and
to process the results.

The basis for any application is the so-called model_definition.xlsx, which can be created either manually or automatically. When creating manually, the model_definition.xlsx must be filled in as described below (see model definition). In case of automatic creation, the Upscaling-Tool (see upscaling tool) is used. After the model_definition.xlsx is filled in, the Main Application (main application) can be started. The structure of the GUI can be seen in the following figure. The sidebar is used to enter input data. The main page is used for descriptions or for displaying results.

Main Application¶

The figure shows which steps must be done for optimize an energy system model. At the bottom of the side bar you will find a button that deletes all stored data such as time series reduction values.

1. Adding the model definition¶

Here you can upload your model_definition.xlsx. After the file has been uploaded, you can theoretically continue with step 5. However, it is useful to make settings to reduce the computing time, since only limited computing resources are available.

2. Preprocessing¶

There are several ways to simplify the model. The method can be found here: ^ Modeling Method. In the following, only the application is briefly described.

Timeseries Simplificaton¶

Depending on which of the time series preparation algorithms described in the methods section is used, the following specifications must be made:

Algorithm: Indication of the simplification algorithm to be applied.
Index: Algorithm specific configuration.
Criterion: Criterion according to which cluster algorithms are applied.
Period: Time periods which are clustered together (weeks, days, hours)
Season: Time periods within which clustering takes place (year, seasons, months)

The following algorithms are applicable and must be specified with the following additional information. A detailed description of the algorithms can be found in the methods section.

Description of the different algorithm.¶
algorithm	description	index	criterion	period	season
k_means	The k-means algorithm clusters the time periods (see period) in such a way; that the squared deviation of the cluster centers is minimal. From the time periods of one cluster the mean is calculated and returned as reference period of the cluster. For the decision the vector of a single parameter (see criterion) over the period duration is considered.	number of clusters to be considered. The number of clusters equals the number of returned reference days.	Clustering criterion to be considered (temperature; dhi; heat demand; electricity demand)	Period length to be clustered (hours; days; or weeks)	–
averaging	successive time periods (e.g. two consecutive days) are averaged and combined into one segment.	number of periods to be averaged	–	length of periods to be averaged (hours; days; weeks)	–
slicing A	every n-th period is selected and considered within the modeling	index = n (every n-th period is selected in the modeling)	–	length of periods to be sliced (hours; days; weeks)	–
slicing B	every n-th period is deleted and removed from the modeling	index = n (every n-th period is removed)	–	length of periods to be sliced (hours; days; weeks)	–
downsampling A	Adaption of the temporal resolution. Every n-th period (selected by index column) is used for the modeling. For example; the resolution can be changed from a 1-hourly to a 3-hourly (index = 3) temporal resolution [1].	index = n (setting the new resolution)	–	–	–
downsampling B	Adaption of the temporal resolution. Every n-th period (selected by index column) is deleted for the modeling.	index = n (determination of the time steps to be deleted)	–	–	–
heuristic selection	representative time periods of a time series are selected from certain selection criteria	applied selection scheme (available schemes are listed here	–	length of periods to be selected (days or weeks)	–
random sampling	a given number of random periods are selected and used as representatives	number of periods to be selected.	–	length of periods to be selected randomly (days or weeks	–

Pre-Modeling Settings¶

Activate Pre-Modeling: If activated, the modeling process is divided into a pre-model and a main-model run.
Investment Boundaries Tightening: Must be checked, if the investment boundaries in the main-model shall be tightened based on the pre-model results.
Investment Tightening Faktor: All investment limits of the main-model are limited to the investment decisions made in the pre-model run multiplied by this factor. If a originally defined investment boundary is lower than this value, the limit will not be changed.
Time Series Simplification: Timeseries simplification for the pre-model have to be set (see above for detailed description).

Pareto Point Options¶

Choose pareto point(s) if you want to start an pareto optimization run. The chosen value defines the constraint reduction in percent referring to the cost minimal pareto point. The values are given in percent.

Advances District Heating Precalculation¶

Clustering District Heating Network: The function allows to group the consumers of a street section into a clustered consumer when optimizing the heat network. This consumer is positioned at the averaged location.
Activate District Heating Precalculations: With use of this function it is possible to use the result folder of a model definition after the first optimization to skip the perpendicular foot print search by using the already existing calculations (this is usually quite time-consuming). For this purpose, the result folder must be specified in the drop-down menu below.

Switch Criteria¶

If you activate this field, you set instead of the primary costs (e. g. monetary costs), the constraining costs (e. g. GHG-Emissions) as the optimization variable, so you perform an e. g. emission-optimized run. The field is intended for single-criteria optimization only. In case of multi-criteria optimization, the optimization criteria will be changed automatically.

3. Processing¶

Number of threads: Number of threads to use for the model run on your machine. You should make sure that the chosen solver supports enough threats (cbc: max. 1 (if no parallelized version), gurobi: max. 8).
Optimization Solver: Chose on of the supported solver. Make sure that the solver is configurated on your machine. We recommend using the gurobi solver if you can use an academic licence.

4. Postprocessing¶

Create xlsx-files: Must be checked, if you want to get result files of every bus. The field should only be checked if users have in-depth model knowledge.

5. Starting the optimization¶

The button starts the optimization. After the optimization process you will be automatically redirected to the Result Processing page.

Model Definition¶

For the modeling and optimization of an energy system, parameters for all system components must be given in the model generator using the enclosed .xlsx file (editable with Excel, LibreOffice, …). The .xlsx file is divided into nine input sheets. In the “energysystem” sheet, general parameters are defined for the time horizon to be examined, in the sheets “buses”, “sinks”, “sources”, “transformers”, “storages” and “links” corresponding components are defined. In the sheet “time series”, the performance of individual components can be stored. In the “weather data” sheet, the required weather data is stored. When completing the input file, it is recommended to enter the energy system step by step and to perform test runs in between, so that potential input errors are detected early and can be localized more easily. In addition to the explanation of the individual input sheets, an example energy system is built step by step in the following subchapters. The input file for this example is stored in the program folder “examples” and viewed on GitHub. The following units are used throughout:

capacity/performance in kW,
energy in kWh,
angles in degrees, and
costs in cost units (CU).

Cost units are any scalable quantity used to optimize the energy system, such as euros or grams of carbon dioxide emissions.

Energysystem¶

Within this sheet, the time horizon and the temporal resolution of the model is defined. The following parameters have to be entered:

start date: Start of the modelling time horizon. Format: “YYYY-MM-DD hh:mm:ss”;
end date: End date of the modelling time horizon. Format: “YYYY-MM-DD hh:mm:ss”; and
temporal resolution: For the modelling considered temporal resolution. Possible inputs: “a” (years), “d” (days), “h” (hours) “min” (minutes), “s” (seconds), “ms” (milliseconds).
timezone: By specifying the timezone, energy systems with correct time series (e.g. relevant for the correct balancing of the PV yield) can be modeled anywhere in the world. For this purpose, the pandas timezone string (e.g. Europe/Berlin) is inserted into the column. Then the weather data, which are available in the weather data sheet in UTC form, are corrected to the considered location.
periods: Number of periods within the time horizon (one year with hourly resolution equals 8760 periods).
cost limit in (CU): Value in order to set a limit for the whole energysystem, e.g. monetary costs. Set this field to “None” in order to ignore the limit. If you want to set a limit, you have to set specific values for each components seen below.
constraint cost limit in (CU): Value in order to set a limit for the whole energysystem, e.g. carbon dioxide emissions. Set this field to “None” in order to ignore the limit. If you want to set a limit, you have to set specific values for each components seen below.
minimum final energy reduction in (kWh): This value can be used to define how much final energy reduction must be achieved. Thus, the optimization algorithm is forced to save at least <your_value_here> kWh of final energy amount. Currently only insulation investments can be used to achieve reductions. The “constraint2” factor of the insulation measures is 1, since every kWh saved by insulation measures is fully included in the savings. This value is set in the algorithm and can currently not be changed by the user.
weather data lat: Latitude (WGS84) of the area under investigation. This value is used to import weather data from Open Energy Platform using feedinlib’s OpenFred.
weather data lon: Longitude (WGS84) of the area under investigation. This value is used to import weather data from Open Energy Platform using feedinlib’s OpenFred.

Exemplary input for the energy system¶
start date	end date	timezone	temporal resolution	periods	cost limit	constraint cost limit	minimum final energy reduction	weather data lat	weather data lon
				(CU)
2012-01-01 00:00:00	2012-12-30 23:00:00	Europe/Berlin	h	8760	None	None	None	None	None

Competition Constraints¶

The spreadsheet “Competition Constraints” allows you to match two components against a predefined limit. For example, an area competition. If you do not want to use this spreadsheet, it simply remains empty. To use this worksheet, the following values must be filled in:

label: Unique designation of the competition constraint.
comment: Space for an individual comment.
component 1: First component that lays claim to the parameter which size set as the limit.
factor 1: Factor that defines how many units of the target unit component 1 needs to provide 1 kW of power.
component 2: Second component that lays claim to the parameter which size set as the limit.
factor 2: Factor that defines how many units of the target unit component 2 needs to provide 1 kW of power.
limit: Maximum size suitable for providing power (e.g. roof area for providing electricity and heat).

Exemplary input for the competition constraints sheet¶
label	comment	component 1	factor 1	component 2	factor 2	limit
			unit/KW		unit/kW	unit
ID_competition		ID_photovoltaic_electricity_source	5.26	ID_solar_thermal_source	1.79	168

Buses¶

Within this sheet, the buses of the energy system are defined. The following parameters need to be entered:

label: Unique designation of the bus. The following format is recommended: “ID_energy sector_bus”.
comment: Space for an individual comment, e.g. an indication of which measure this component belongs to.
active: Specifies whether the bus shall be included to the model. 0 = inactive, 1 = active.
excess: Specifies whether a sink is to be generated, which consumes excess energy. 0 = no excess sink will be generated; 1 = excess sink will be generated.
shortage: Specifies whether to generate a shortage source that can compensate energy deficits or not. 0 = no shortage source will be generated; 1 = shortage source will be generated.
excess costs in (CU/kWh): Assigns a price per kWh to the release of energy to the excess sink. If the excess sink was deactivated, the fill character “0” is used.
shortage costs in (CU/kWh): Assigns a price per kWh to the purchase of energy from the shortage source. If the shortage source was deactivated, the fill character “0” is used.
excess constraint costs in (CU/kWh): Assigns a price per kWh to the release of energy to the excess sink referring to the constraint limit set in the “energysystem” sheet. If the excess sink was deactivated, the fill character “0” is used. If not considering constraints fill character “0” is used.
shortage constraint costs in (CU/kWh): Assigns a price per kWh to the purchase of energy from the shortage source referring to the constraint limit set in the “energysystem” sheet. If the shortage source was deactivated, the fill character “0” is used. If not considering constraints fill character “0” is used.
district heating conn.: This column allows you to specify whether the bus should be connected to the heating network. If not, select 0. If yes, either the nearest point of the heating network can be used as a connection (in this case the column must be filled with “dh-system”), or one of the street points from the “District Heating” sheet is used (in this case the column must be filled according to the following pattern: street-label-1 for the first node or street-label-2 for the second).
lat: This column must be filled if dh-system was specified in the “district heating conn.” column. In this case, this column must be filled with the latitude (WGS84).
lon: This column must be filled if dh-system was specified in the “district heating conn.” column. In this case, this column must be filled with the longitude (WGS84).
sector: This column is used to assign the shortages of the buses to the energy amount diagrams in the result processing. Possible entries: electricity, heat, cooling, central_electricity, central_heat, central_cooling and None for buses that cannot be assigned to any category.

Exemplary input for the buses sheet¶
label	comments	active	excess	shortage	excess costs	shortage costs	excess constraint costs	shortage constraint costs	district heating conn.	lat	lon	sector
					(CU/kWh)	(CU/kWh)	(CU/kWh)	(CU/kWh)
ID_electricity_bus		1	0	1	0.000	0.300	0.00	474.00	0	0	0	electricity
ID_heat_bus		1	1	0	0.000	0.000	0.00	0.00	0	0	0	heat
ID_gas_bus		1	0	1	0.000	0.070	0.00	0.00	0	0	0	None
ID_cooling_bus	chiller	1	1	0	0.000	0.000	0.00	0.00	0	0	0	cooling
ID_pv_bus		1	1	0	-0.068	0.000	-56.00	0.00	0	0	0	electricity
ID_hp_electricity_bus	heat pumps	1	1	1	0.000	0.220	0.00	474.00	0	0	0	electricity
district_electricity_bus	delivering electr. to neighb. subsystems	0	0	0	0.000	0.000	0.00	0.00	0	0	0	central_electricity
district_heat_bus	delivering heat to neighb. subsystems	0	0	0	0.000	0.000	0.00	0.00	dh-system	50.000000	10.000000	central_heat
district_chp_electricity_bus		0	0	1	0.000	0.000	-375.00	0.00	0	0	0	central_electricity
district_gas_bus		0	0	1	0.000	0.070	0.00	0.00	0	0	0	None

Bus_Graph — Graph of the energy system, which is created by entering the example components. The non-active components are not included in the graph above.¶

District Heating¶

Within this sheet, the road network structure of the energy system is defined. The following parameters need to be entered:

label: Unique designation of the street section, e.g. the street section name.
comment: Space for an individual comment.
active: Specifies whether the street section shall be included to the model. 0 = inactive, 1 = active.
lat. 1st intersection: Latitude (WGS84) of the first point of the given street part.
lon. 1st intersection: Longitude (WGS84) of the first point of the given street part.
lat. 2nd intersection: Latitude (WGS84) of the second point of the given street part.
lon. 2nd intersection: Longitude (WGS84) of the second point of the given street part.

Exemplary input for the district heating sheet¶
label	comment	active	lat. 1st intersection	lon. 1st intersection	lat. 2nd intersection	lon. 2nd intersection

street1		1	50.000000	10.000000	55.000000	11.000000

Sinks¶

Within this sheet, the sinks of the energy system are defined. The following parameters need to be entered:

label: Unique designation of the sink. The following format is recommended: “ID_energy sector_sink”.
comment: Space for an individual comment, e.g. an indication of which measure this component belongs to.
active: Specifies whether the sink shall be included to the model. 0 = inactive, 1 = active.
fixed: Indicates whether it is a fixed sink or not. 0 = not fixed; 1 = fixed.
input: Specifies the bus from which the input to the sink comes from.
load profile: Specifies the basis onto which the load profile of the sink is to be created. If the Richardson tool is to be used, “richardson” has to be inserted. For standard load profiles, its acronym is used. If a time series is used, “timeseries” must be entered and must be provided in the Time series sheet. If the sink is not fixed, the fill character “x” has to be used.
nominal value in (kW): Nominal performance of the sink. Required when “timeseries” has been entered into the “load profile”. When SLP or Richardson is used, use the fill character “0” here.
annual demand in (kWh/a): Annual energy demand of the sink. Required when using the Richardson Tool or standard load profiles. When using time series, the fill character “0” is used.
occupants [RICHARDSON]: Number of occupants living in the respective building. Only required when using the Richardson tool, use fill character “0” for other load profiles.
building class [HEAT SLP ONLY]: BDEW building classes that coincide with the building locations are explained here.
wind class [HEAT SLP ONLY]: Wind classification for building location (0=not windy, 1=windy).
sector: This column is used to assign the sinks’ energy amounts to the energy amount diagrams in the result processing. Possible entries: electricity, heat, cooling.

Exemplary input for the sinks sheet¶
label	comment	active	fixed	input	load profile	nominal value	annual demand	occupants	building class	wind class	sector
						(kW)	(kWh/a)	(richardson)	(heat slp)	(heat slp)
ID_electricity_sink	H0 standard load profile sink	1	1	ID_electricity_bus	h0	0	5000.0	0	0	0	electricity
ID_heat_sink	EFH standard load profile sink	1	1	ID_heat_bus	efh	0	30000.0	0	3	0	heat
ID_cooling_sink	fixed timeseries cooling demand	0	1	ID_cooling_bus	timeseries	1	0	0	0	0	cooling

Sink_Graph — Graph of the energy system, which is created by entering the example components. The non-active components are not included in the graph above.¶

Sources¶

Within this sheet, the sources of the energy system are defined. Technology specific data (see 2nd line), must be filled in only if the respective technology is selected otherwise use 0. The following parameters have to be entered:

label: Unique designation of the source. The following format is recommended: “ID_energy sector_source”.
comment: Space for an individual comment, e.g. an indication of which measure this component belongs to.
active: Specifies whether the source shall be included to the model. 0 = inactive, 1 = active.
fixed: Indicates whether it is a fixed source or not. 0 = not fixed; 1 = fixed.
output: Specifies which bus the output of the source is connected to.
inout: Specifies which bus the input of the source is connected to (only needed for solar heat).
technology: Technology type of source. Input options: “photovoltaic”, “windpower”, “timeseries”, “other”, “solar_thermal_flat_plate”, “concentrated_solar_power”. Time series are automatically generated for photovoltaic systems and wind turbines. If “timeseries” is selected, a time series must be provided in the Time series sheet.
sector: This column is used to differentiate between an electricity, heat and cooling timeseries source for the result processing’s energy amount collection. Possible entries: electricity, heat, cooling, central_electricity, central_heat, central_cooling.

Costs¶

existing capacity in (kW): Existing capacity of the source before possible investments.
min. investment capacity in (kW): Minimum capacity to be installed in case of an investment.
max. investment capacity in (kW): Maximum capacity that can be added in the case of an investment. If no investment is possible, enter the value “0” here.
variable costs in (CU/kWh): Defines the variable costs incurred for a kWh of energy drawn from the source.
variable constraint costs in (CU/kWh): Defines the variable costs incurred for a kWh of energy drawn from the source referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.
periodical costs in (CU/(kW a)): Costs incurred per kW for investments within the time horizon. Periodical costs only apply for newly invested capacities but not for existing capacities.
periodical constraint costs in (CU/(kW a)): Costs incurred per kW for investments within the time horizon referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.
Non-Convex Investment: Specifies whether the investment capacity should be defined as a mixed-integer variable, i.e. whether the model can decide whether NOTHING OR THE INVESTMENT should be implemented. Explained here.
Fix Investment Costs in (CU/a): Fixed costs of non-convex investments (in addition to the periodic costs).
Fix Investment Constraint Costs in (CU/a): Fixed constraint costs of non-convex investments (in addition to the periodic costs)

Wind¶

The following parameters need to be set for wind sources.

The wind speed timeseries entered in the sheet “weather data” (measured at 10 m height) will get converted into wind speeds at specified hub height. With the specified turbine model an energy timeseries will then be calculated.

Turbine Model: Reference wind turbine model. Possible turbine types are listed in the windpowerlib’s database. Write the value of the column “turbine_type” of the .csv in your spreadsheet.
Hub Height: Hub height of the wind turbine. Which hub heights are possible for the selected reference turbine can be viewed in the windpowerlib’s database too.

PV¶

The following parameters need to be set for PV sources.

Modul Model: Module name, according to the database used (see PVLIB database). Possible Modul Models are presented here.
Inverter Model: Inverter name, according to the database used. Possible Inverter Models are presented here.
Azimuth: Specifies the orientation of the PV module in degrees. Values between 0 and 360 are permissible (0 = north, 90 = east, 180 = south, 270 = west). Use fill character “0” for other technologies.
Surface Tilt: Specifies the inclination of the module in degrees (0 = flat). Use fill character “0” for other technologies.
Albedo: Specifies the albedo value of the reflecting floor surface. Only required for photovoltaic sources, use fill character “0” for other technologies.
Altitude: Height (above mean sea level) in meters of the photovoltaic module. Only required for photovoltaic sources, use fill character “0” for other technologies.
Latitude: Geographic latitude (decimal number) of the photovoltaic module. Only required for photovoltaic sources, use fill character “0” for other technologies.
Longitude: Geographic longitude (decimal number) of the photovoltaic module. Only required for photovoltaic sources, use fill character “0” for other technologies.

Concentrated Solar Power¶

The following parameters need to be set for concentrated solar power sources.

Azimuth: Specifies the orientation of the PV module in degrees. Values between 0 and 360 are permissible (0 = north, 90 = east, 180 = south, 270 = west). Use fill character “0” for other technologies.
Surface Tilt: Specifies the inclination of the module in degrees (0 = flat). Use fill character “0” for other technologies.
ETA 0: Optical efficiency of the collector. Use fill character “0” for other technologies.
A1: Collector specific linear heat loss coefficient. Use fill character “0” for other technologies.
A2: Collector specific quadratic heat loss coefficient. Use fill character “0” for other technologies.
C1: Collector specific thermal loss parameter. Only required for concentrated solar power source, use fill character “0” for other technologies.
C2: Collector specific thermal loss parameter. Only required for concentrated solar power source, use fill character “0” for other technologies.
Temperature Inlet in (°C): Inlet temperature of the solar heat collector module. Use fill character “0” for other technologies.
Temperature Difference in (°C): Temperature Difference between in- and outlet temperature of the solar heat collector module. Use fill character “0” for other technologies.
Cleanliness: Cleanliness of a parabolic through collector. Only required for Concentrated Solar Power source, use fill character “0” for other technologies.
Electric Consumption: Electric consumption of the collector system. Example: If value is set to 0,05, the electric consumption is 5 % of the energy output. Use fill character “0” for other technologies.
Peripheral Losses: Heat loss coefficient for losses in the collector’s peripheral system. Use fill character “0” for other technologies.

Exemplary values for concentrated_solar_power technology:

Exemplary values for concentrated_solar_power technology (The parameters refer to Janotte, N; et al)¶
Cleanliness	ETA 0	A1	A2	C1	C2
solar heat	solar heat	solar heat	solar heat	solar heat	solar heat
0.9	0.816	-0.00159	0.0000977	0.0622	0.00023

Solar Thermal Flatplate¶

The following parameters need to be set for solar thermal flatplate sources.

Azimuth: Specifies the orientation of the PV module in degrees. Values between 0 and 360 are permissible (0 = north, 90 = east, 180 = south, 270 = west). Use fill character “0” for other technologies.
Surface Tilt: Specifies the inclination of the module in degrees (0 = flat). Use fill character “0” for other technologies.
ETA 0: Optical efficiency of the collector. Use fill character “0” for other technologies.
A1: Collector specific linear heat loss coefficient. Use fill character “0” for other technologies.
A2: Collector specific quadratic heat loss coefficient. Use fill character “0” for other technologies.
Temperature Inlet in (°C): Inlet temperature of the solar heat collector module. Use fill character “0” for other technologies.
Temperature Difference in (°C): Temperature Difference between in- and outlet temperature of the solar heat collector module. Use fill character “0” for other technologies.
Electric Consumption: Electric consumption of the collector system. Example: If value is set to 0,05, the electric consumption is 5 % of the energy output. Use fill character “0” for other technologies.
Peripheral Losses: Heat loss coefficient for losses in the collector’s peripheral system. Use fill character “0” for other technologies.
Conversion Factor in m²/kW: The factor is explained here.

Timeseries¶

If you have chosen the technology “timeseries” (in the technology column), you have to include a timeseries in the Time series sheet or use default one.

Commodity¶

If you have chosen the technology “other” (in the technology column), a commodity source with maximum investable capacity but completely variable time series becomes part of the energy system. The solver can thus design a completely linear source and use it to cover the demand when required.

Exemplary input for the sources sheet¶
label	active	fixed	technology	output	input	existing capacity	min. investment capacity	max. investment capapcity	non-convex investment	fix investment costs	variable costs	periodical costs	variable constraint costs	periodical constraint costs	Turbine Model	Hub Height	technology database	inverter database	Modul Model	Inverter Model	Albedo	Altitude	Azimuth	Surface Tilt	Latitude	Longitude	ETA 0	A1	A2	C1	C2	Temperature Inlet	Temperature Difference	Conversion Factor	Peripheral Losses	Electric Consumption	Cleanliness	sector
					solar heat	(kW)	(kW)	(kW)		(CU/a)	(CU/kWh)	(CU/(kW a))	(CU/kWh)	(CU/(kW a))	windpower	windpower	PV	PV	PV	PV	PV	(m)\| PV	(°)	(°)	(°)	(°)	solar heat	solar heat	solar heat	solar heat	solar heat	(°C) \| solar heat	(°C)\|solar heat	(sqm/kW) \| solar heat	solar heat	solar heat	solar heat
ID_photovoltaic_electricity_source	1	1	photovoltaic	ID_pv_bus	None	0	0	20	0	0	0	90	56	0	0	0	SandiaMod	sandiainverter	Panasonic_VBHN235SA06B__2013_	ABB__MICRO_0_25_I_OUTD_US_240__240V_	0.18	60	180	35	52.13	7.36	0	0	0	0	0	0	0	0	0	0	0	electricity
ID_solar_thermal_source	1	1	solar_thermal_flat_plate	ID_heat_bus	ID_electricity_bus	0	0	20	0	0	0	40	25	0	0	0	0	0	0	0	0	0	20	10	52.13	7.36	0.719	1.063	0.005	0	0	40	15	1.79	0.05	0.06	0	heat
wind_turbine	0	1	windpower	electricity_bus	None	0	0	30	0	0	0	100	9	0	E-126/4200	135	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	electricity

Source_Graph — Graph of the energy system, which is created by entering the example components of sources sheet. The non-active components are not included in the graph above.¶

Transformers¶

Within this sheet, the transformers of the energy system are defined.

The following parameters have to be entered:

label: Unique designation of the transformer. The following format is recommended: “ID_energy sector_transformer”.
comment: Space for an individual comment, e.g. an indication of which measure this component belongs to.
active: Specifies whether the transformer shall be included to the model. 0 = inactive, 1 = active.
transformer type: Indicates what kind of transformer it is. Possible entries: “GenericTransformer” for linear transformers with constant efficiencies; “GenericTwoInputTransformer” for transformers with two inputs and constant efficiencies (e. g. Pumping units with water and electricity intake); “GenericCHP” for transformers with varying efficiencies; “CompressionHeatTransformer”; “AbsorptionHeatTransformer”.
mode: Specifies, if a compression or absorption heat transformer is working as “chiller” or “heat_pump”. Only required if “transformer type” is set to “CompressionHeatTransformer” or “AbsorptionHeatTransformer”. Otherwise has to be set to “None”, “none”, “0”.
input: Specifies the bus from which the input to the transformer comes from.
input2: Specifies the bus from which the input2 to the transformer comes from. Only required if “transformer type” is set to “GenericTwoInputTransformer”. If there is no second input, the fill character “0” must be entered here.
output: Specifies bus to which the output of the transformer is forwarded to. For CHP Transformers it should be the electric output.
output2: Specifies the bus to which the output of the transformer is forwarded to, if there are several outputs. If there is no second output, the fill character “0” must be entered here.
input2 / input: Specifies the ratio of input2 to input (e. g. kWh/m³). Only required if “transformer type” is set to “GenericTwoInputTransformer”. If there is no second input, the fill character “0” must be entered here.
sector: This column is used to differentiate the transformer types for the result processing’s energy amount collection. Possible entries: electricity, heat, cooling, central_electricity, central_heat, central_cooling, electric_heating.
technology: The technology column represents the category for collecting the energy amounts for the energy amount diagrams. Attention: If at sector central_… is used, a leading “central_” will be added to the selected technology in the balancing.

Costs¶

variable input costs in (CU/kWh): Variable costs incurred per kWh of input energy supplied.
variable input costs 2 in (CU/kWh): Variable costs incurred per kWh of input2 energy supplied.
variable output costs in (CU/kWh): Variable costs incurred per kWh of output energy supplied.
variable output costs 2 in (CU/kWh): Variable costs incurred per kWh of output 2 energy supplied.
variable input constraint costs in (CU/kWh): Variable constraint costs incurred per kWh of input energy supplied referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.
variable input constraint costs 2 in (CU/kWh): Variable constraint costs incurred per kWh of input2 energy supplied referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.
variable output constraint costs in (CU/kWh): Variable constraint costs incurred per kWh of output energy supplied referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.
variable output constraint costs 2 in (CU/kWh): Variable constraint costs incurred per kWh of output 2 energy supplied referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.
existing capacity in (kW): Already installed capacity of the transformer.
min investment capacity in (kW): Minimum transformer capacity to be installed.
max investment capacity in (kW): Maximum installable transformer capacity regarding the output of the transformer, in addition to previously installed capacity, if existing.
periodical costs in (CU/a): Costs incurred per kW for investments within the time horizon. Periodical costs only apply for newly invested capacities but not for existing capacities.
periodical constraint costs in (CU/(kW a)): Constraint costs incurred per kW for investments within the time horizon. If not considering constraints fill character “0” is used.
Non-Convex Investment: Specifies whether the investment capacity should be defined as a mixed-integer variable, i.e. whether the model can decide whether NOTHING OR THE INVESTMENT should be implemented. Explained here.
Fix Investment Costs in (CU/a): Fixed costs of non-convex investments (in addition to the periodic costs).
Fix Investment Constraint Costs in (CU/a): Fixed constraint costs of non-convex investments (in addition to the periodic costs).

Generic Transformer¶

efficiency: Specifies the efficiency of the first output. Values between 0 and 1 are allowed entries.
efficiency2: Specifies the efficiency of the second output, if there is one. Values between 0 and 1 are entered. If there is no second output, the fill character “0” must be entered here.

Compression Heat Transformer¶

The following parameters are only required, if “transformer type” is set to “CompressionHeatTransformer”:

heat source: Specifies the heat source. Possible heat sources are “GroundWater”, “Ground”, “Air”, “Air-to-Air” (which represents an AAHP) and “Water” possible.
temperature high in (°C): Temperature of the high temperature heat reservoir. Only required if “mode” is set to “heat_pump”.
temperature low in (°C): Cooling temperature needed for cooling demand. Only required if “mode” is set to “chiller”.
quality grade: To determine the COP of a real machine a scale-down factor (the quality grade) is applied on the Carnot efficiency (see oemof.thermal).
area in (sqm): Open spaces for ground-coupled compression heat transformers (GC-CHT).
length of the geoth. probe in (m): Length of the vertical heat exchanger, only for GC-CHT.
heat extraction in (kW/(m*a)): Heat extraction for the heat exchanger referring to the location, only for GC-CHT.
min. borehole area in (sqm): Limited space due to the regeneation of the ground source, only for GC-CHT.
temp threshold icing: Temperature below which icing occurs (see oemof.thermal). Only required if “mode” is set to “heat_pump”.
factor icing: Factor to which the COP is reduced caused by icing (e.g. 0.8 if you have a reduction of 20%). (see oemof.thermal). Only required if “mode” is set to “heat_pump”.

Absorption Heat Transformer¶

The following parameters are only required, if “transformer type” is set to “AbsorptionHeatTransformer”:

name: Defines the way of calculating the efficiency of the absorption heat transformer. Possible inputs are: “Rotartica”, “Safarik”, “Broad_01”, “Broad_02”, and “Kuehn”. “Broad_02” refers to a double-effect absorption chiller model, whereas the other keys refer to single-effect absorption chiller models.
temperature high in (°C): Temperature of the heat source, that drives the absorption heat transformer.
temperature low in (°C): Output temperature which is needed for the cooling demand.
electrical input conversion factor: Specifies the relation of electricity consumption to energy input. Example: A value of 0,05 means, that the system comsumes 5 % of the input energy as electric energy.
recooling temperature difference in (°C): Defines the temperature difference between temperature source for recooling and recooling cycle.
heat capacity of source: Defines the heat capacity of the connected heat source e.g. extracted waste heat.

GenericCHP¶

Warning

Currently the GenericCHP component can only be used for the purpose of simulation. The solver is not able to dimension the components capacity. Since there is no investment decision no periodical costs apply.

min. share of flue gas loss: Percentage flue gas losses of the operating point with maximum heat extraction.
max. share of flue gas loss: Percentage flue gas losses of the operating point with minimum heat extraction.
min. electric power in (kW): Minimum electrical power supply without heat extraction (district heating).
max. electric power in (kW): Maximum electrical power supply without heat extraction (district heating).
min. electric efficiency: Specifies the minimum electric efficiency without heat extraction (district heating). Values between 0 and 1 are allowed entries.
max. electric efficiency: Specifies the minimum electric efficiency without heat extraction (district heating). Values between 0 and 1 are allowed entries.
minimal thermal output power in (kW): Heat output taken from the exhaust gas via a condenser even in purely electric operation.
electric power loss index: Reduction of the electrical power by “electric power loss index * extracted thermal power”.
back pressure: Defines rather the end pressure of “Turbine CHP” is higher than ambient pressure (input value has to be “1”) or not (input value has to be “0”). For “Motoric CHP” it has to be “0”.

Exemplary input for the transformers sheet¶
label	comment	active	transformer type	mode	input	input2	output	output2	input2 / input	efficiency	efficiency2	existing capacity	min. investment capacity	max. investment capacity	non-convex investment	fix investment costs	variable input costs	variable input costs 2	variable output costs	variable output costs 2	periodical costs	variable input constraint costs	variable input constraint costs 2	variable output constraint costs	variable output constraint costs 2	periodical constraint costs	heat source	temperature high	temperature low	quality grade	area	length of the geoth. probe	heat extraction	min. borehole area	temp. threshold icing	factor icing	name	electrical input conversion factor	recooling temperature difference	min. share of flue gas loss	max. share of flue gas loss	min. electric power	max. electric power	min. electric efficiency	max. electric efficiency	minimal thermal output power	elec. power loss index	back pressure	sector	technology
												(kW)	(kW)	(kW)		(CU/a)	(CU/kWh)	(CU/kWh)	(CU/kWh)	(CU/kWh)	(CU/(kW a))	(CU/kWh)	(CU/kWh)	(CU/kWh)	(CU/kWh)	(CU/(kW a))		(°C)	(°C)		(m²)	(m)	(kW/(m*a))	(m²)	(°C)				(°C)			(kW)	(kW)			(kW)
ID_gasheating_transformer		1	GenericTransformer	0	ID_gas_bus	0	ID_heat_bus	None	0	0.85	0	10	0	20	0	0	0	0	0	0	70	0	0	200	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	heat	natural_gasheating
ID_TwoInput_transformer	high pressure pump	0	GenericTwoInputTransformer	None	ID_water_intake_bus	ID_electricity_intake_bus	ID_water_output_bus	None	0.84	0.88	0	0	0	4000	0	0	0	0	0	0	6.600	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	None	None
ID_GCHP_transformer	ground-coupled heat pump	1	CompressionHeatTransformer	heat_pump	ID_hp_electricity_bus	0	ID_heat_bus	None	0	1	0	0	0	20	0	0	0	0	0	0	115.57	0	0	0	0	0	Ground	60	0	0.6	1000	100	0.05	100	3	0.8	0	0	0	0	0	0	0	0	0	0	0	0	heat	GCHP
ID_ASCH_transformer	air source chiller	1	CompressionHeatTransformer	chiller	ID_hp_electricity_bus	0	ID_cooling_bus	None	0	1	0	0	0	20	0	0	0	0	0	0	100	0	0	0	0	0	Air	0	-10	0.4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	cooling	ASCH
ID_AbsCH_transformer	absorption chiller	1	AbsorptionHeatTransformer	chiller	ID_hp_electricity_bus	0	ID_cooling_bus	None	0	1	0	0	0	20	0	0	0	0	0	0	100	0	0	0	0	0	0	85	10	0	0	0	0	0	0	0	Kuehn	0.05	6	0	0	0	0	0	0	0	0	0	cooling	AbsCH
ID_ASHP_transformer	air source heat pump	1	CompressionHeatTransformer	heat_pump	ID_hp_electricity_bus	0	ID_heat_bus	None	0	1	0	0	0	20	0	0	0	0	0	0	112.78	0	0	0	0	0	Air	60	0	0.4	0	0	0	0	3	0.8	0	0	0	0	0	0	0	0	0	0	0	0	heat	ASHP
ID_chp_transformer		0	GenericTransformer	0	district_gas_bus	0	district_chp_electricity_bus	district_heat_bus	0	0.35	0.55	0	0	20	0	0	0	0	0	0	50	130	0	375	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	heat	natural_gas_CHP

Transformer_Graph — Graph of the energy system, which is created by entering the example components. The non-active components are not included in the graph above.¶

Storages¶

Within this sheet, the storages of the energy system are defined. The following parameters have to be entered:

label: Unique designation of the storage. The following format is recommended: “ID_energy sector_storage”.
comment: Space for an individual comment, e.g. an indication of which measure this component belongs to.
active: Specifies whether the storage shall be included to the model. 0 = inactive, 1 = active.
storage type: Defines whether the storage is a “Generic” or a “Stratified” sorage. These two inputs are possible.
bus: Specifies which bus the storage is connected to.
input/capacity ratio (invest): Indicates the performance with which the storage can be charged (see also here).
output/capacity ratio (invest): Indicates the performance with which the storage can be discharged (see also here).
efficiency inflow: Specifies the charging efficiency.
efficiency outflow: Specifies the discharging efficiency.
initial capacity: Specifies how far the storage is loaded at time 0 of the simulation. Value must be between 0 and 1. The initial capacity value must be equal or higher than the ‘capacity min’ value.
capacity min: Specifies the minimum amount of storage that must be loaded at any given time. Value must be between 0 and 1.
capacity max: Specifies the maximum amount of storage that can be loaded at any given time. Value must be between 0 and 1.
sector: This column is used to differentiate between an electricity, heat and cooling storages for the result processing’s energy amount collection. Possible entries: electricity, heat, cooling, central_electricity, central_heat, central_cooling.

Costs¶

existing capacity in (kW): Previously installed capacity of the storage.
min. investment capacity in (kW): Minimum storage capacity to be installed.
max. investment capacity in (kW): Maximum in addition to existing capacity, installable storage capacity.
Non-Convex Investment: Specifies whether the investment capacity should be defined as a mixed-integer variable, i.e. whether the model can decide whether NOTHING OR THE INVESTMENT should be implemented. Explained here.
Fix Investment Costs in (CU/a): Fixed costs of non-convex investments (in addition to the periodic costs)
Fix Investment Constraint Costs in (CU/a): Fixed constraint costs of non-convex investments (in addition to the periodic costs)
variable input costs: Indicates how many costs arise for charging with one kWh.
variable output costs: Indicates how many costs arise for charging with one kWh.
periodical costs in (CU/a): Costs incurred per kW for investments within the time horizon. Periodical costs only apply for newly invested capacities but not for existing capacities.
variable input constraint costs: Indicates how many costs arise for charging with one kWh referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.
variable output constraint costs: Indicates how many costs arise for charging with one kWh referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.
periodical constraint costs in (CU/a): Costs incurred per kW for investments within the time horizon referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.

Generic Storage¶

capacity loss (Generic only): Indicates the percentage storage loss per time unit. Only required, if the “storage type” is set to “Generic”.

Stratified Storage¶

diameter in (m) | (Stratified Storage): Defines the diameter of a stratified thermal storage, which is necessary for the calculation of thermal losses.
temperature high in (°C) | (Stratified Storage): Outlet temperature of the stratified thermal storage.
temperature low in (°C) | (Stratified Storage): Inlet temperature of the stratified thermal storage.
U value in (W/(sqm*K)) | (Stratified Storage): Thermal transmittance coefficient

Exemplary input for the storages sheet¶
label	active	storage type	bus	input/capacity ratio	output/capacity ratio	efficiency inflow	efficiency outflow	initial capacity	capacity min	capacity max	existing capacity	min. investment capacity	max. investment capacity	non-convex investment	fix investment costs	variable input costs	variable output costs	periodical costs	variable input constraint costs	variable output constraint costs	periodical constraint costs	capacity loss	diameter	temperature high	temperature low	U value	sector
				(invest)	(invest)						(kWh)	(kWh)	(kWh)		(CU/a)	(CU/kWh)	(CU/kWh)	(CU/(kWh a))	(CU/kWh)	(CU/kWh)	(CU/(kWh a))	Generic Storage	(m) \| Stratified Storage	(°C) \| Stratified Storage	Stratified Storage	(W/(m²*K)) \| Stratified Storage
ID_battery_storage	1	Generic	ID_electricity_bus	0.17	0.17	1	0.98	0	0.1	1	0	0	100	0	0	0	0	70	0	0	400	0	0	0	0	0	electricity
ID_thermal_storage	1	Generic	ID_heat_bus	0.17	0.17	1	0.98	0	0.1	0.9	0	0	100	0	0	0	20	35	0	0	100	0	0	0	0	0	heat
ID_stratified_thermal_storage	0	Stratified	ID_heat_bus	0.2	0.2	1	0.98	0	0.05	0.95	0	0	100	0	0	0	20	35	0	0	100	0	0.8	60	40	0.04	heat
district_battery_storage	0	Generic	district_electricity_bus	0.17	0.17	1	0.98	0	0.1	1	0	0	1000	0	0	0	0	10	0	0	10	0	0	0	0	0	central_electricity

Links¶

Within this sheet, the links of the energy system are defined. The following parameters have to be entered:

label: Unique designation of the link. The following format is recommended: “ID_energy sector_transformer”
comment: Space for an individual comment, e.g. an indication of which measure this component belongs to.
active: Specifies whether the link shall be included to the model. 0 = inactive, 1 = active.
bus1: First bus to which the link is connected. If it is a directed link, this is the input bus.
bus2: Second bus to which the link is connected. If it is a directed link, this is the output bus.
(un)directed: Specifies whether it is a directed or an undirected link. Input options: “directed”, “undirected”.
efficiency: Specifies the efficiency of the link. Values between 0 and 1 are allowed entries.

Costs¶

variable output costs in (CU/kWh): Specifies the efficiency of the first output. Values between 0 and 1 are allowed entries.
variable output constraint costs in (CU/kWh): Costs incurred per kWh referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.
existing capacity in (kW): Already installed capacity of the link.
min. investment capacity in (kW): Minimum, in addition to existing capacity, installable capacity.
max. investment capacity in (kW): Maximum capacity to be installed.
periodical costs in (CU/(kW a)): Costs incurred per kW for investments within the time horizon. Periodical costs only apply for newly invested capacities but not for existing capacities.
periodical constraint costs in (CU/(kW a)): Costs incurred per kW for investments within the time horizon. Periodical constraint costs only apply for newly invested capacities but not for existing capacities.
Non-Convex Investment: Specifies whether the investment capacity should be defined as a mixed-integer variable, i.e. whether the model can decide whether NOTHING OR THE INVESTMENT should be implemented. Explained here.
Fix Investment Costs in (CU/a): Fixed costs of non-convex investments (in addition to the periodic costs).
Fix Investment Constraint Costs in (CU/a): Fixed constraint costs of non-convex investments (in addition to the periodic costs)

Exemplary input for the link sheet¶
label	active	(un)directed	bus1	bus2	efficiency	existing capacity	min. investment capacity	max. investment capacity	non-convex investment	fix investment costs	variable output costs	periodical costs	variable constraint costs	periodical constraint costs
						(kW)	(kW)	(kW)		(CU/a)	(CU/kWh)	(CU/(kW a))	(CU/kWh)	(CU/(kW a))
ID_pv_to_ID_electricity_link	1	directed	ID_pv_bus	ID_electricity_bus	1	0	0	0	0	0	0	0	0	0
ID_electricity_to_ID_hp_electricity_bus	1	directed	ID_electricity_bus	ID_hp_electricity_bus	1	0	0	0	0	0	0	0	0	0
districtheat_directed_link	0	directed	district_heat_bus	ID_heat_bus	0.85	0	0	0	0	0	0	0	0	0
districtheat_undirected_link	0	undirected	district_heat_bus	ID_heat_bus	0.85	0	0	0	0	0	0	0	0	0
district_electricity_link	0	directed	district_electricity_bus	ID_electricity_bus	1	0	0	0	0	0	0.1438	0	0	0
district_chp_to_district_electricity_bus	0	directed	district_chp_electricity_bus	district_electricity_bus	1	0	0	0	0	0	0.1438	0	0	0
ID_pv_to_district_electricity_link	0	directed	ID_pv_bus	ID_electricity_bus	1	0	0	0	0	0	0.1438	0	0	0

bsp-graph-link — Graph of the energy system, which is created by entering the example components. The non-active components are not included in the graph above.¶

Insulation¶

Within this sheet, the energy system insulation options are defined. The following parameters have to be entered:

label: Unique designation of the insulation. The following format is recommended: “ID_sink_label_insulation_type”
comment: Space for an individual comment, e.g. an indication of which measure this component belongs to.
active: Specifies whether the insulation shall be included to the model. 0 = inactive, 1 = active.
existing: Existing represents a boolean decision (0=no, 1=yes). If a 1 is filled in here, the insulation measure is completely implemented without incurring any costs.
sink: Sink influenced by the insulation.
temperature indoor in (°C): Definition of the living space temperature.
heat limit temperature in (°C): Temperature from which the heating is switched on.
U-value old in (W/(m² *K)): U-value before insulation.
U-value new in (W/(m² *K)): U-value after insulation.
area in (m²): Area that can be considered for isolation.
periodical costs in (CU/(m² *a)): Costs incurred per m² for investments within the time horizon.
periodical constraint costs in (CU/(m² *a)): Costs incurred per m² for investments within the time horizon referring to the constraint limit set in the “energysystem” sheet. If not considering constraints fill character “0” is used.

Time Series¶

Within this sheet, time series of components of which no automatically created time series exist, are stored. More specifically, these are sinks to which the property “load profile” have been assigned as “timeseries” and sources with the “technology” property “timeseries”. The following parameters have to be entered:

timestamp: Points in time to which the stored time series are related. Should be within the time horizon defined in the sheet “timesystem”.
timeseries: Time series of a sink or a source which has been assigned the property “timeseries” under the attribute “load profile” or “technology. Time series contain a value between 0 and 1 for each point in time, which indicates the proportion of installed capacity accounted for by the capacity produced at that point in time. In the header line, the name must rather be entered in the format “componentID.fix” if the component enters the power system as a fixed component or it requires two columns in the format “componentID.min” and “componentID.max” if it is an unfixed component. The columns “componentID.min/.max” define the range that the solver can use for its optimisation.

Exemplary input for time series sheet¶
timestamp	residential_electricity_demand.actual_value	fixed_timeseries_electricty_source.fix	unfixed_timeseries_electricty_source.max	fixed_timeseries_electricity_sink.fix	unfixed_timeseries_electricity_sink.max	fixed_timeseries_cooling_demand_sink.fix
2012-01-01 00:00:00	0.559061982	0.000000	1.000000	0.000000	1.000000	100
2012-01-01 01:00:00	0.533606486	0.041667	0.500000	0.041667	0.500000	100
2012-01-01 02:00:00	0.506058757	0.083333	0.333333	0.083333	0.333333	100
2012-01-01 03:00:00	0.504140877	0.125000	0.250000	0.125000	0.250000	100
2012-01-01 04:00:00	0.507104873	0.166667	0.200000	0.166667	0.200000	100
2012-01-01 05:00:00	0.511376515	0.208333	0.166667	0.208333	0.166667	100
2012-01-01 06:00:00	0.541801064	0.250000	0.142857	0.250000	0.142857	100
2012-01-01 07:00:00	0.569261616	0.291667	0.125000	0.291667	0.125000	100
2012-01-01 08:00:00	0.602998867	0.333333	0.111111	0.333333	0.111111	100
2012-01-01 09:00:00	0.629064598	0.375000	0.100000	0.375000	0.100000	100

Weather Data¶

If electrical load profiles are simulated with the Richardson tool, heating load profiles with the demandlib or photovoltaic systems with the feedinlib, weather data must be stored here. The weather data time system should be in conformity with the model’s time system, defined in the sheet “timesystem”.

timestamp: Points in time to which the stored weather data are related.
dhi: Diffuse horizontal irradiance in W/m².
dni: Direct normal irradiance in W/m².
ghi: Global horizontal irradiance in W/m².
pressure: Air pressure in Pa.
temperature: Air temperature in °C.
windspeed: Wind speed, measured at 10 m height, in unit m/s.
z0: Roughness length of the environment in units m.
ground_temp: Constant ground temperature at 100 m depth.
water_temp: Varying water temperature of a river depending on the air temperature.
groundwater_temp: Constant temperatur of the ground water at 6 - 10 m depth in North Rhine-Westphalia.

Exemplary input for weather data¶
timestamp	dhi	dirhi	pressure	temperature	windspeed	z0	ground_temp	water_temp	groundwater_temp
2012-01-01 00:00:00	0.00	0.00	98405.70	10.33	7.2	0.15	13.7	14.62	13.06
2012-01-01 01:00:00	0.00	0.00	98405.70	10.33	7.8	0.15	13.7	14.62	13.06
2012-01-01 02:00:00	0.00	0.00	98405.70	10.48	7.7	0.15	13.7	14.71	13.06
2012-01-01 03:00:00	0.00	0.00	98405.70	10.55	7.7	0.15	13.7	14.75	13.06
2012-01-01 04:00:00	0.00	0.00	98405.70	10.93	7.8	0.15	13.7	14.99	13.06
2012-01-01 05:00:00	0.00	0.00	98405.70	10.90	8.5	0.15	13.7	14.97	13.06
2012-01-01 06:00:00	0.00	0.00	98405.70	10.88	8.5	0.15	13.7	14.96	13.06
2012-01-01 07:00:00	0.00	0.00	98405.70	11.22	7.9	0.15	13.7	15.17	13.06
2012-01-01 08:00:00	0.00	0.00	98405.70	11.68	8.7	0.15	13.7	15.46	13.06
2012-01-01 09:00:00	0.56	0.56	98405.70	11.87	8.6	0.15	13.7	15.57	13.06
2012-01-01 10:00:00	13.06	13.06	98405.70	11.65	8.0	0.15	13.7	15.44	13.06

Upscaling Tool¶

The Upscaling-Tool simplifies the creation of the model definition. For more information take a look at the method: Modeling Method.

1. Uploading the upscaling sheet¶

Upload your upscaling_sheet.xlsx which contains all building-specific parameters.

2. Uploading the standard parameter sheet¶

Upload your standard_parameter.xlsx which contains all technological parameters.

3. Naming the model definition¶

You can choose any name for your model definition.

4. Starting the Upscaling-Tool¶

The model definition is created automatically and can be viewed on the right side.

5. Downloading the xlsx-file¶

If you agree with the model definition, it can be downloaded. The model definition serves as a basis for the optimization process and can be used on the Main Application.

Upscaling Sheet¶

This part of the documentation is taken from Budde’s master’s thesis [1] and guides how the upscaling sheet can be adapted.

Category 1¶

Input for the upscaling sheet. Category 1: Building-specific data.¶
label	active	year of construction	distance of electric vehicles	electricity demand	heat demand	building type	units	occupants per unit	gross building area	latitude	longitude	year of construction wall	area outer wall	year of construction windows	area windows	year of construction roof	rooftype	area roof	cluster ID	flow temperature	electricity cost	heatpump electricity cost	electricity emission	heatpump electricity emission
x			km/a	kWh / (sqm * a)	kWh / (sqm * a)				sqm	° WGS 84	° WGS 84		sqm		sqm			sqm		°C	€/kWh	g/kWh	€/kWh	g/kWh
001_building	1	1800	0	400	400	COM_Food	1	1	100	52.000000	7.000000	1800	50	0	0	1967	flat roof	25	0	60	standard	standard	standard	standard
002_building	1	1800	0	0	0	MFB	1	1	50	52.000000	7.000000	1979	100	1999	20	1993	flat roof	50	0	60	standard	standard	standard	standard
003_building	1	1800	10000	30	20	SFB	1	1	120	52.000000	7.000000	1994	250	2001	125	1992	step roof	125	0	40	standard	standard	standard	standard

label: The building name can be chosen by the user and is the identification number (ID) of a building. The ID must be unique for each building, because all the following columns are assigned to it.
comment: Space for an individual comment, e.g. an indication of which measure this component belongs to.
active: In this cell, users decide whether a building should be considered in the modeling.
year of construction: The year of construction of a building is relevant for the calculation of the heat demand.
distance of electric vehicles (km/a): The annual kilometers driven are used to create the charging profile of an electric car. The electricity demand for the electric car is considered separately from the building electricity demand.
electricity demand (kWh / (m² a)): The specific electricity demand is multiplied by the useful building area to calculate the annual demand. If the annual electricity demand is not available as a function of the building floor area, 1 m² must be entered for the building floor area.
heat demand (kWh / (m² a)): The specific heat demand is multiplied by the useful building area to calculate the annual demand. If the annual heat demand is not available as a function of the building floor area, 1 m² must be entered for the building floor area.
building type: The building usage influences the calculation of the energy demand and the selection of the load profile for buildings. The different building types can be found in the standard parameter documentation (see standard parameter). The following input values are valid: SFB, MFB, COM_Food, COM_Retail, COM_Office, COM_School, COM_Stable, COM_Sports, COM_Workshop, COM_Restaurant and COM_Hotel.
units: The number of housing units is required for calculating the heat demand of residential buildings.
occupants per unit: The occupants per housing unit are required to calculate the electricity demand of the households. If the occupants per housing unit are multiplied by the housing units, the number of occupants per building can be calculated. The summed occupants of all buildings represent the total modeled neighborhood residents and provide a good basis for validation with real data.
gross building area (m²): The gross building area is required to calculate the annual electricity and heat demand of commercial buildings and the heat demand of residential buildings. For this purpose, the gross building area is multiplied by the specific electricity and heat demand and a building area factor (see standard parameter). The building area factor depends on the building use and reduces the gross building area by non-usable areas such as the base areas of walls.
latitude (° WGS 84): The latitude of the building are required to connect the building to a heating network. In addition, the coordinates are used to obtain weather data for PV systems from an external database. The World Geodetic System 1984 (WGS 84) is used as a reference system.
longitude (° WGS 84): The longitude of the building are required to connect the building to a heating network. In addition, the coordinates are used to obtain weather data for PV systems from an external database. The World Geodetic System 1984 (WGS 84) is used as a reference system.
year of construction wall: The year of construction of a walls is relevant for the calculation of the savings potential of insulation measures. For each building, the U-value (also heat transfer coefficient) is obtained from the standard parameter sheet (see standard parameter), depending on the year of construction of the building. In the Energy Saving Ordinance 2014, U-values are defined to achieve the desirable efficiency level 1. These U-values can be maximally achieved in the modeling. The difference between current and minimum U-value is the possible saving of heat demand. The calculation is explained in the standard parameter documentation (see standard parameter).
area outer wall (m²): The external wall area is relevant for the calculation of insulation measures.
year of construction windows: The year of construction of windows is relevant for the calculation of the savings potential of insulation measures. For each building, the U-value (also heat transfer coefficient) is obtained from the standard parameter sheet (see standard parameter), depending on the year of construction of the building. In the Energy Saving Ordinance 2014, U-values are defined to achieve the desirable efficiency level 1. These U-values can be maximally achieved in the modeling. The difference between current and minimum U-value is the possible saving of heat demand. The calculation is explained in the standard parameter documentation (see standard parameter).
area windows (m²): The window area is relevant for the calculation of insulation measures.
year of construction roof: The year of construction of a roof is relevant for the calculation of the savings potential of insulation measures. For each building, the U-value (also heat transfer coefficient) is obtained from the standard parameter sheet (see standard parameter), depending on the year of construction of the building. In the Energy Saving Ordinance 2014, U-values are defined to achieve the desirable efficiency level 1. These U-values can be maximally achieved in the modeling. The difference between current and minimum U-value is the possible saving of heat demand. The calculation is explained in the standard parameter documentation (see standard parameter).
rooftype: The roof type is differentiated between flat roofs and step roofs. The roof type is relevant for the calculation of insulation measures.
area roof (m²): The roof areas are relevant for the calculation of insulation measures.
cluster ID: The cluster ID is used to spatially assign a building to a specific area. The area can be, for example, a settlement or neighborhood. The cluster ID is crucial for spatial clustering.
flow temperature (°C): The flow temperature may differ depending on the heating system. The flow temperature should not fall below the heat source temperature of a heat pump. If the outdoor temperature is 35 °C and the flow temperature is 30 °C, the air heat pump is switched off and an alternative technology is used for heat supply.
electricity cost (€/kWh): If the user wants to use a electricity purchase price that differs from the standard parameter (e.g. due to a green electricity tariff), this can be entered here. If not the user has to enter “standard”.
electricity emission (g/kWh): If the user wants to use a electricity purchase emission that differs from the standard parameter (e.g. due to a green electricity tariff), this can be entered here. If not the user has to enter “standard”.
heatpump electricity cost (€/kWh): If the user wants to use a heatpump electricity purchase price that differs from the standard parameter (e.g. due to a different heatpump tariff), this can be entered here. If not the user has to enter “standard”.
heatpump electricity emission (g/kWh): If the user wants to use a heatpump electricity purchase emission that differs from the standard parameter (e.g. due to a different heatpump tariff), this can be entered here. If not the user has to enter “standard”.

Category 2¶

Input for the upscaling sheet. Category 2: Building investment data.¶
label	HS	ashp	gchp	parcel ID	oil heating	gas heating	battery storage	thermal storage	central heat	electric heating	wood stove	aahp	st 1	pv 1	roof area 1	surface tilt 1	azimuth 1	st 2	pv 2	roof area 2	surface tilt 2	azimuth 2
x															(m²)	(°)	(°)			(m²)	(°)	(°)
001_building	1	no	no	no	no	no	no	no	yes	no	yes	yes	no	no	0	0	0	no	no	0	0	0
002_building	1	no	no	no	no	yes	no	no	no	no	yes	yes	yes	yes	150	75	100	0	0	0	0	0
003_building	1	yes	yes	GCHP25	no	no	yes	yes	yes	no	yes	yes	yes	yes	200	50	180	0	0	0	0	0

label: The building name can be chosen by the user and is the identification number (ID) of a building. The ID must be unique for each building, because all the following columns are assigned to it.
ashp: Air source heat pumps (ASHP) can be considered in the optimization of a building if the air-regenerated noise of the fans does not exceed the limits of the Technical Instructions on Noise Abatement (TA Lärm). There are already some ASHP on the market that meet the requirements.
gchp: Ground-coupled heat pumps are limited by the area required for geothermal collectors or probes. If there is a potential area for the GCHP, the so-called parcel must be assigned to the buildings.
parcel ID: The parcel ID assigns a potential area for GCHP to the buildings. On an additional auxiliary data sheet, users enter the parcel ID and the potential area.
heat extraction (kW/m): The extraction capacity of the geothermal probes or collectors is crucial for the performance of the heat pumps. The extraction rate should be determined specifically for the location.
oil heating, gas heating, electric heating, battery storage, thermal storage, wood stove, aahp: The technologies are not subject to restrictions and can be considered as an investment alternative.
central heat: If a heating network is available, a network connection can be considered as an investment alternative.
wood stove share: If a value between 0 and 1 is used as “wood stove share”, this share is separated from the main household heat demand and connected primarily to the wood stove. To avoid insolubility, this bus is also connected to the main heating bus of the considered building. If this division of the sink is not desired, “standard” should be used.
solar thermal share: If a value between 0 and 1 is used as “solar thermal share”, this share is separated from the main household heat demand and connected primarily to the solar thermal collector. To avoid insolubility, this bus is also connected to the main heating bus of the considered building. If this division of the sink is not desired, “standard” should be used.
st 1: In this column it is decided whether the roof potential area applies to solar thermal (ST) systems. Possible entries: yes or no.
pv 1: In this column it is decided whether the roof potential area applies to photovoltaic (PV) systems. Possible entries: yes or no. As soon as both systems are relevant for one area, an area competition arises, which is automatically considered.
roof area 1 (m²): The roof potential area of a building can be divided into several partial roof areas with respect to the radiation intensity. In total, users can add 30 partial roof areas.
surface tilt 1 (°): The surface tilt is decisive for the dimensioning of the solar systems and depends on the construction of the roof.
azimuth 1 (°): The azimuth is also critical to solar system sizing and depends on the orientation of the building.

Category 3¶

Input for the upscaling sheet. Category 3: Central investment data.¶
label	comment	active	technology	latitude	longitude	area	dh_connection	azimuth	surface tilt	flow temperature	length of the geoth. probe	heat extraction
				° WGS 84	° WGS 84	sqm		°	°	°C	m	(kW / (m*a))
electricity_exchange		1	electricity_exchange
battery_storage		1	battery
ng_chp		0	naturalgas_chp				heat_input
bg_chp		0	biogas_chp				heat_input
pe_chp		0	pellet_chp				heat_input
wc_chp		1	woodchips_chp				heat_input
swhp		0	swhp_transformer				heat_input
ashp		0	ashp_transformer				heat_input
gchp	free area needed	1	gchp_transformer			2500	heat_input				100	0.0328
ng_heating		0	naturalgas_heating_plant				heat_input
bg_heating		0	biogas_heating_plant				heat_input
pe_heating		0	pellet_heating_plant				heat_input
wc_heating		1	woodchips_heating_plant				heat_input
thermal_storage		1	thermal_storage				heat_input
p2g		0	power_to_gas				heat_input
heat_input	heat center	1	heat_input_bus	52	7					40
central_pv_st	free area needed	1	pv&st	52	7	15000	heat_input	180	22.5
screw_turbine		1	timeseries_source

label: The technology name can be chosen arbitrarily by the user and represents the ID of a central technology. The ID must be unique for each technology, because all following columns are assigned to it.
comment: Space for an individual comment, e.g. an indication of which measure this component belongs to.
active: In this cell, users decide whether a technology should be considered in the modeling.
technology: In this cell, the central technologies are considered (see table below).
latitude, longitude (° WGS 84): The WGS 84 coordinates are required when heat grid centers or ground-mounted solar systems are selected as technologies. The coordinates are used to locate the technologies.
area (m²): This is where the area for central solar and GCHP systems is entered.
dh_connection: In this cell, the central heat supply technologies are connected to a heat network center. The label of the heat network center must be entered. In addition, the corner points of the street pipes must be located in the auxiliary data sheet. Two WGS 84 coordinates are required for each corner point. The length of the house connection lines (distance between distribution line and house connection point) is calculated automatically. With the perpendicular point method, the shortest path for the house connection lines is always calculated. Twelve different pipe diameters are stored in the standard parameter sheer (see standard parameter), which can be considered as investment alternatives.
azimuth (°): For ground-mounted solar systems, the azimuth must be specified.
surface tilt (°): For ground-mounted solar systems, the surface tilt must be specified.
flow temperature (°C): For each heat network center, it is necessary to specify the flow temperature at which the technologies feed into the heat network.
length of the geoth. probe (m): For GCHP systems it is necessary to specify the length of the vertical heat exchanger.
heat extraction (kW / (m*a)): For GCHP systems it is necessary to specify the heat extraction for the heat exchanger.

All possible central technologies.¶
key word	meaning
electricity_exchange	local energy market
battery	battery storage
naturalgas_chp	natrual gas combined heat and power (CHP)
biogas_chp	biogas CHP
pellet_chp	pellet CHP
woodchips_chp	woodchip CHP
swhp_transformer	surface water heat pump (SWHP)
ashp_transformer	ASHP
gchp_transformer	GCHP
naturalgas_heating_plant	natural gas heating plant
biogas_heating_plant	biogas heating plant
pellet_heating_plant	pellet heating plant
woodchips_heating_plant	woodchips heating plant
thermal_storage	central thermal storage
power_to_gas	Power-to-Gas system (electrolyzer; hydrogen storage; fuel cell; methanation; natural gas storage)
heat_input_bus	heat network center
pv&st	central photovoltaic or solar thermal system
timeseries_source	time series e.g. hydropower plants

Category 4¶

Input for the upscaling sheet. Category 4: Time series.¶
timestamp	dhi	pressure	temperature	windspeed	z0	dni	ghi	ground_temp	water_temp	groundwater_temp	screw_turbine.fix	electric_vehicle.fix
01.01.2012 00:00	0	100119.3125	8.656125	5.9235	0.159	0	0	12.6	14.62006667	13.06	0.420911041	0
01.01.2012 01:00	0	100113.836	8.9435	6.455	0.159	0	0	12.6	14.62006667	13.06	0.420911041	0
01.01.2012 02:00	0	100102.5625	9.210125	6.8535	0.159	0	0	12.6	14.71342667	13.06	0.420911041	0
01.01.2012 03:00	0	100075.5	9.6415	7.318	0.159	0	0	12.6	14.75492	13.06	0.420911041	0
01.01.2012 04:00	0	100026.8555	9.9285	7.916	0.159	0	0	12.6	14.99350667	13.06	0.420911041	0
…	…	…	…	…	…	…	…	…	…	…	…	…

timestamp: The time stamp is entered with an hourly accuracy for one year (8 760 time steps). All further time series are assigned to this time stamp.
temperature (°C), dhi (W/m²), dni (W/m²), ghi (W/m²), pressure (Pa), windspeed (m/s), z0 (m): The time series can be obtained from the Open Energy Platform via the Open Fred interface integrated in the SESMG. For this purpose, the year and the centroid of the neighborhood are specified in the Graphical User Interface (GUI). The outdoor temperature (temperature) serves as a heat source for ASHP, influences the performance of the PV systems and has an impact on the heat transfer of the building components. Diffuse horizontal irradiance (dhi), direct normal irradiance (dni) and global horizontal irradiance (ghi) are required for solar systems. The air pressure (pressure), wind speed (windspeed), and surface roughness (z0) are required for wind turbines. In addition, the air pressure influences the design of the PV systems. Alternatively, the time series can be taken from other sources and added to the upscaling sheet.
ground_temp: The ground temperature serves as a heat source for GCHP.
water_temp: The water temperature serves as a heat source for SWHP.
groundwater_temp: The ground-water temperature serves as a heat source for ground-water heat pumps (GWHP).
screw_turbine.fix: This is a dimensionless time series that indicates the relative utilization of the hydropower screw. Multiplication by the maximum electrical power gives the power per time step.
electric_vehicle.fix: The time series represents the charging power of an electric car. Each time series value is automatically multiplied by the annual kilometers driven and transferred to the model_definition.xlsx.

Standard Parameter Sheet¶

The standard parameter sheet contains all technology-specific data (costs, emissions, efficiencies) as well as all other data (e.g. specific energy requirements) required for energy system modeling. The parameters used are included in the following standard parameter documentation: https://doi.org/10.5281/zenodo.6974401

The documents contain all values, formulas and related sources used. The standard parameter documentation is intended to ensure the reproducibility of the results. The documentation is continuously updated.

References¶

[1] Budde J., Leitfaden zur Modellierung von Energiesystemen (2022), master thesis.

[2] Klemm, C., Budde J., Vennemann P., Model Structure for urban energy system optimization models, unpublished at the time of publication of this documentation, 2021.

Results¶

Warning

If a time series preparation algorithm was applied for the (main-)model, not every time-step of the model was modeled. This must be considered when analysing energy amounts. Simplifying, it can be assumed that the modeled amount of energy multiplied by the variable cost factor (see methods section) corresponds to the actual amount of energy over the entire period. Changes in the cost structure, on the other hand, are automatically taken into account.

Interactive Results¶

You will be automatically directed to this page after the optimization process (1) or you may want to analyze existing results (2) again.

1. Result processing after optimization process¶

The results differ depending on whether you used only one optimization criterion (a) or whether you did a multi-criteria optimization (b).

1a. Single-criteria optimization¶

In a single-criteria optimization, the costs, emissions, and energy demands of the neighborhood are displayed. In addition, you can view the system graph and all building-specific load profiles via the interactive results.

1b. Multi-criteria optimization¶

In multi-criteria optimization, several scenarios are calculated. For more information take a look at the method: Modeling Method. For each scenario, the results described for a single-criteria optimization can be displayed by selecting the reduction of the scenario (see (1) figure below). In addition, a Pareto diagram and energy amount diagrams are displayed (see (2) figure below).

2. Result processing of existing results¶

The difference is that you need to select a folder that you want to analyze.

Results as Spreadsheets and Log-Files¶

The results of the modeling are stored in the “results” folder in two formats: - as summarizing log files, under - as detailed xlsx-files.

The log-file gives an overview of which components are created and which of the investment options should be implemented. In addition, it is indicated which costs for the supply of the energy system are incurred in the optimized case. For each implemented bus, an xlsx-file is created in which incoming and outgoing energy flows are specified for each time step of the model are.

Technical Data¶

Within the technical data section advanced model settings can be adjusted.

heuristic selection patterns¶

Within the ‘hierarchical_selection_schemes.xlsx’-file custom patterns for heuristic selection can be defined.

The xlsx-file contains an individual sheet for each applicable heursitic selection pattern. Each sheet is named with an integer number, which corresponds to the index with which the pattern can be selected during modeling. New patterns can be added as desired. Each pattern contains a list of reference periods, which are selected during the heuristic selection. The following information is stored for each reference period:

period: indicates from what period the reference period will be selected. Possible values are: year, winter, spring, summer, fall, integer number between 1 and 12.
criterion: indicates which parameter the selection of the reference period is based on. Possible values are: temperature, dhi, el_demand_sum, heat_demand_sum
value: indicates, whether the lowest, the highest or the most average value of the selected criterion within the selected period will be chosen. Possible values are: lowest, highest, average
average/extreme: indicates whether extreme values or average values of a reference period will be considered. For example, whether the period with the highest (value=highest) maximum (average/extreme=extreme) temperature (criterion=temperature) or the highest (value=highest) average (average/extreme=average) temperature (criterion=temperature) will be selected. Possible values are: extreme, average

characteristic_parameters¶

A database of absorption chillers has been created in the characteristic_parameters file. This can be extended by the user if required.

Warning

This database was taken from the examples of oemof thermal it is therefore not occupied by the developing team of the SESMG. A description of the parameters can be taken from oemof.thermal and papers by Ziegler.