The Spreadsheet Energy System Model Generator¶

About the Model Generator¶

The Spreadsheet Energy System Model Generator allows the modeling and optimization of energy systems without the need for programming skills. The components defined in this spreadsheet are defined with the included Python program and the open source Python library “oemof”, assembled to an energy system and optimized with the open source solver “cbc”. The modeling results can be viewed and analyzed using a browser-based results output.

Structure of Energy Systems¶

Energy systems in the sense of the Spreadseet Energy System Model Generator are designed according to the specifications of the oemof library. Accordingly, energy systems can be represented with the help of mathematical graph theory. Thus, energy systems are exemplified as “graphs” consisting of sets of “vertices” and “edges”. In more specific terms, vertices stand for components and buses while directed edges connect them. The status variable of the energy flow indicates which amount of energy is transported between the individual nodes at what time. Possible components of an oemof energy system are

sources,
sinks,
transformers, and
storages.

Buses furthermore form connection points of an energy system. The graph of a simple energy system consisting of each one source, one transformer, one sink, as well as two buses, could look like the example displayed in the following figure.

Graph of a simple energy system, consisting of one source, two buses, one transformer, and one a sink.

An oemof energy system must be in equilibrium at all times. Therefore sources must always provide exactly as much energy as the sinks and transformer losses consume. In turn, the sink must be able to consume the entire amount of energy supplied. If there is no balance, oemof is not able to solve the energy system.

Buses¶

The modelling framework oemof does not allow direct connections between components. Instead, they must always be connected with a bus. The bus in turn can be connected to other components, so that energy can be transported via the bus. Buses can have any number of incoming and outgoing flows. Buses can not directly be connected with each other. They do not consider any conversion processes or losses.

Sources¶

Sources represent the provision of energy. This can either be the exploitation of of an energy source (e.g. gas storage reservoir or solar energy, no energy source in physical sense), or the simplified energy import from adjacent energy systems. While some sources may have variable performances, depending on the temporary needs of the energy system, others have fixed performances, which depend on external circumstances. In the latter case, the exact performances must be entered to the model in form of time series. With the help of oemofs “feedinlib” and “windpowerlib”, electrical outputs of photovoltaik (pv)-systems and wind power plants can be generated automatically. In order to ensure a balance in the energy system at all times, it may be useful to add a “shortage” source to the energy system, which supplies energy in the event of an energy deficit. In reality, such a source could represent the purchase of energy at a fixed price.

Photovoltaic Systems

The following Figure sketches the fractions of radiation arriving at a PV-module as well as further relevant parameters.

Radiation on a photovoltaic module.

The global radiation is composed of direct and diffuse radiation. The “direct horizontal irradiance” dirhi is the amount of sun radiation as directly received by a horizontal surface. The “diffuse horizontal irradiance” dhi is the share of radiation, which arrives via scattering effects on the same surface. A part of the global radiation is reflected on the ground surface and can thus cause an additional radiation contribution on the photovoltaic module. The amount of the reflected part depends on the magnitude of the albedo of the ground material. Exemplary albedo values are listed in the following table.

Sinks¶

Sinks represent either energy demands within the energy system or energy exports to adjacent systems. Like sources, sinks can either have variable or fixed energy demands. Sinks with variable demands adjust their consumption to the amount of energy available. This could for example stand for the sale of surplus electricity. However, actual consumers usually have fixed energy demands, which do not respond to amount of energy available in the system. As with sources, the exact demands of sinks can be passed to the model with the help of time series.

In order to ensure a balance in the energy system at all times, it may be appropriate to add an “excess” sink to the energy system, which consumes energy in the event of energy surplus. In reality, this could be the sale of electricity or the give-away of heat to the atmosphere.

Standard Load Profiles

Oemof’s sub-library demandlib can be used for the estimation of heat and electricity demands of different consumer groups, as based on German standard load profiles (SLP). The following electrical standard load profiles of the Association of the Electricity Industry (VDEW) can be used:

Profil	Consumer Group
H0	households
G0	commercial general
G1	commercial on weeks 8-18 h
G2	commercial with strong consumption in the evening
G3	commercial continuous
G4	shop/hairdresser
G5	bakery
G6	weekend operation
L0	agriculture general
L1	agriculture with dairy industry/animal breeding
L2	other agriculture

The following heat standard load profiles of the Association of Energy and Water Management (BDEW) can be used:

Profile	House Type
EFH	single family house
MFH	multi family house
GMK	metal and automotive
GHA	retail and wholesale
GKO	Local authorities, credit institutions and insurance companies
GBD	other operational services
GGA	restaurants
GBH	accommodation
GWA	laundries, dry cleaning
GGB	horticulture
GBA	bakery
GPD	paper and printing
GMF	household-like business enterprises
GHD	Total load profile Business/Commerce/Services

In addition, the location of the building and whether the building is located in a “windy” or “non-windy” area are taken into account for the application of heat standard load profiles. The following location classes may be considered:

Stochastic Load Profiles (Richardson Tool)

The use of standard load profiles has the disadvantage that they only represent the average of a larger number of households (> 200). Load peaks of individual households (e.g. through the use of hair dryers or electric kettles) are filtered out by this procedure. To counteract this, the Spreadsheet Energy System Model Generator offers the possibility to generate stochastic load profiles for residential buildings. These are generated on the basis of Richardsonpy. Thereby, an arbitrary number of different realistic load profiles is simulated under consideration of statistic rules. The mean value of a large-enough number of profiles should, again, result in the standard load profile. However, if calculations are continued using the individual values before averaging – as in the above calculation of costs – different values are obtained than when calculating with SLPs.

Transformers¶

Transformers are components with one ore more input flows, which are transformed to one or more output flows. Transformers may be power plants, energy transforming processes (e.g., electrolysis, heat pumps), as well as transport lines with losses. The transformers’ efficiencies can be defined for every time step (e.g., the efficiency of a thermal powerplants in dependence of the ambient temperature).

Currently only Generic Transformers can be used within the Spreadsheet Energy System Model Generator. These may have one or more different outputs, e.g., heat and electricity. For the modelling, the nominal performance of a generic transformer with several outputs, the respective output ratios, and an efficiency for each output need to be known.

Links¶

Links can be used to connect two buses or to display transport losses of networks. Links are not represented by a separate oemof class, they are rather represented by transformers. In order to map a loss-free connection between two buses, an efficiency of 1 is used. If a link is undirected, a separate transformer must be used for each direction. In an energy system, links can represent, for example, electrical powerlines, gas pipelines, district heating distribution networks or similar.

Representation of directed and undirected links with oemof transformers

Storages¶

Storages are connected to a bus and can store energy from this bus and return it to a later point in time.

Investment¶

The investment costs help to compare the costs of building new components to the costs of further using existing components instead. The annual savings from building new capacities should compensate the investment costs. The investment method can be applied to any new component to be built. In addition to the usual component parameters, the maximum installable capacity needs to be known. Further, the periodic costs need to be assigned to the investment costs. The periodic costs refer to the defined time horizon. If the time horizon is one year, the periodical costs correspond to the annualized capital costs of an investment.

Getting Started¶

Installation¶

Warning

Warning! The installation has only been tested under Windows, using Python 3.7.6 (64 bit)! Python 3.8 is currently not supported.

Install Python (version 3.5 or higher)

Note

Make sure to select “Add pyton to PATH” at the beginning of the Python installation.

go to the Python download page
chose a Python version (e.g., “Python 3.7.6”) and klick “download”
download an installer (e.g., “Windows x86-64 executable installer”)
execute the installer on your computer

Download the Spreadsheet Energy System Model Generator from GIT as .zip folder.
Extract the .zip folder into any directory on the computer.
Download the CBC-solver from here
Extract the CBC solver into the folder of the Spreadsheet Energy System Model Generator
Execute the “installation.cmd” file.

Note

If you receive a “Your computer has been protected by Windows” error message, click “More Information,” and then “Run Anyway”.

The Spreadsheet Energy System Model Generator has been installed

Application of the Model Generator¶

Fill in the spreadsheet document according to the instructions in the following chapter and save it as “scenario.xlsx” in the main folder of the Spreadsheet Energy System Model Generator.
Execute the “exe.cmd” file in the main folder of the program.

Note

If you receive a “Your computer has been protected by Windows” error message, click “More Information,” and then “Run Anyway”.

Wait until the modelling is completed. The results are then automatically opened in your Internet browser.
More detailed modelling results are stored within the “results” folder.

Using the Scenario File¶

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 “timesystem” 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 GIT. 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.