Getting started¶

SMOOTH stands for “Simulation Model for Optimized Operation and Topology of Hybrid energy systems”. This tool serves to minimise costs and maximise the sustainability of dynamic energy systems. The key features of SMOOTH are:

The real world energy system is reduced to its relevant components
Detailed modelling of components including non-linear component behaviour, state-dependent component behaviour and tracking arbitrary states of the components
Stepwise simulation without using perfect foresight
Parameter optimization possible in combination with a genetic algorithm

Documentation
Installing smooth
General concept
Structure of the SMOOTH module
Components
Examples
Framework
Optimization
Got further questions on using SMOOTH?
License

Documentation ¶

Full documentation can be found here

Installing smooth ¶

In order to use SMOOTH, the smooth package and its requirements need to be installed. There is the option to clone the current repository of SMOOTH to your local machine using:

git clone https://github.com/rl-institut/smooth

The necessary requirements (found in requirements.txt in repository) are installed into a working Python3 environment by:

pip install -r requirements.txt

SMOOTH is then installed by:

python setup.py install

You also need to install the solver for oemof. This can be done according to this documentation page.

General concept ¶

SMOOTH solves an explicitly defined energy system with several components, such as energy sources, electrolyzers, storages etc. The energy system is parameterized with the help of different input parameters such as investment and operating costs as well as site-related time series with a fixed time resolution. While the components and the algorithm executing the simulation are part of SMOOTH, each component creates a valid oemof model for each time step and the system is solved using oemof-solph. The financial costs/revenues and emissions, where the costs are divided into variable costs, CAPEX and OPEX, are tracked for each component individually. After the simulation, all costs/revenues and emissions are transferred to annuities (kg/a and EUR/a, respectively) based on the component lifetimes, and the total system financial and emissions annuities are recorded. The notable states of the components and the energy and mass flows of the system are also recorded and all results can be saved for later use.

An additional functionality of SMOOTH is the optimization (MOEA) which optimizes the topology and operational management of an energy system with regards to ecological and economic target criteria. Key parameters of components are chosen, such as the maximum power output or capacity, and varied in numerous versions of the energy system until the optimal solution/s is/are reached. The specification of the final system/s is/are finally returned as SMOOTH results.

Structure of the SMOOTH module ¶

The SMOOTH module consists of four sections: components, examples, framework and optimization.

Components ¶

The smooth.components package contains all of the existing components of an energy system that have already been built in SMOOTH, along with any related functions. Input parameters that are defined by the user in the model definition, or by default values that are specified within the component, are used to calculate and determine the behaviour of the component for each timestep. Within each component, an oemof component is created using the parameters defined or calculated in the SMOOTH component to be used later in the oemof model. Visit the section for detailed information on each of the components and how to build a new component.

Examples ¶

In order to get a better, applied understanding of how to define a model, and either run a simulation or an optimization, see the examples directory for examples, and the smooth.examples package for corresponding explanations.

Framework ¶

The smooth.framework package consists of the main function that runs the SMOOTH simulation framework (the run_smooth() function) as well as other functions that are necessary for updating and evaluating the simulation results (in the smooth.framework.functions package). An outline and brief description of the available functions in the framework is presented below:

run_smooth(): the main function which enables the simulation in SMOOTH, and must be called by the user.
calculate_external_costs(): calculates costs for components in the system which are not part of the optimization but their costs should be taken into consideration. This function can be called in the same file as the run_smooth function.
debug(): generates debugging information from the results, and prints, plots and saves them. It is called in the run_smooth function if the user sets the show_debug_flag parameter as True in the simulation parameters.
load_results(): loads the saved results of either a simulation or optimization. Can be called by the user in a file where the results are evaluated.
plot_results(): plots results of a SMOOTH run, which can be called after the simulation/optimization results are obtained.
print_results(): prints the financial results of a SMOOTH run, which can be called after the simulation/optimization results are obtained.
save_results(): saves the results of either a SMOOTH run or an optimization, which can be called after the results are obtained.
update_annuities(): calculates and updates the financial and emission annuities for the components used in the system. It is called in the generic Component class, which is used to define each component.
update_fitted_costs(): calculates the fixed costs and fixed emissions of a component. The user can define the dependencies on certain values using a set of specific fitting methods. This function is also called in the generic Component class, which is used to define each component.