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TESPy: Thermal Engineering Systems in Python |
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18. February 2020 |
paper.bib |
TESPy (Thermal Engineering Systems in Python) provides a powerful simulation toolkit for thermal process engineering, for instance power plants, district heating systems or heat pumps. With the TESPy package it is possible to design plants and simulate stationary operation. From that point, part-load behavior can be predicted using underlying characteristics for each of the plant's components. The component based structure combined with the solution method offer very high flexibility regarding the plant's topology and its parametrisation. An extensive online documentation is provided at @TESPy. Several examples and tutorials on how to use the software are included, too.
Thermal process simulation is a fundamental discipline in energy engineering. Consequently, there are several well known commercial software solutions available in this field, for example EBSILON Professional or Aspen Plus, mainly used in the industrial environment. A similar approach was carried out by @ThermoPower with the open source library "ThermoPower" written in the Modelica language. The software provides dynamic modeling and focuses on steam power plants, but has not been updated since 2014 [@ThermoPowerOnline].
Here we propose a new solution for simulating thermal processes, since ThermoPower is not currently maintained and also limited to one field of thermal engineering. In order to open the software to a wide (scientific) audience an open source solution in the widespread programming language Python is implemented.
TESPy is built up in modular structure with three main modules:
- networks: The networks module represents the container for every simulation. Initialisation, preprocessing, solving and postprocessing are handled by the network class.
- components: All components are part of the components module. The package provides basic components, for example different types of turbomachinery, heat exchangers, pipes, valves and mixers or splitters. On top of that, advanced components like a drum, an internal combustion engine or a combustion chamber are available. The individual properties of each component are defined in the respective class.
- connections: Connections are used to connect components and hold the fluid property information. Thus, they represent the plant's topology and its state.
To simulate a specific plant an individual model is created connecting the
components to form a topological network. Steady state operation of the plant is
determined by the fluid's state on every connection (and therefore its change
within components) between the plant's individual components. Thus, based on the
components and parameters applied, TESPy generates a set of nonlinear equations
representing the plant's topology and its parametrisation. By formulating the
equations implicitly parameters and results are generally interchangeable
offering high flexibility in the user specifications. The system of equations is
numerically solved with an inbuilt solver applying the multi-dimensional
Newton-Raphson method to determine the mass flow
To achieve this, TESPy implements balance equations based on standard literature, for example @Baehr or @Epple, for every component regarding
- mass flow and fluid composition as well as
- energy (covering thermal and hydraulic properties).
On top of the basic equations presented in this paper, there are many component-specific equations that can be applied by the user. The full list of components, its parameters and the respective equations is documented online in the API section [@TESPy]. For calculation of fluid properties TESPy uses CoolProp [@CoolProp], which supports a wide range of pure and incompressible fluids. In case of gaseous mixtures the software calculates the fluid properties by the laws of ideal mixtures [@Baehr; @Herning1936].
In steady state, the total mass flow into a component must be equal to the total
mass flow leaving the component (eq. \ref{eq:1}). Additionally, the mass balance
of a specific fluid
In thermal engineering applications the change in kinetic and potential energy
due to differences in flow velocity
\begin{align} \begin{split} 0 &=\underset{i}{\sum}\dot{m}{\mathrm{in,}i}-\underset{o}{\sum} \dot{m}{\mathrm{out,}o} \label{eq:1} \end{split} \[2ex] \begin{split} 0 &=\underset{i}{\sum}\dot{m}{\mathrm{in,}i}\cdot x{fl\mathrm{,in,}i}- \underset{o}{\sum}\dot{m}{\mathrm{out,}o}\cdot x{fl\mathrm{,out,}o} \ \forall fl\in\mathrm{network\ fluids} \label{eq:2} \end{split} \[2ex] \begin{split} 0 & =\underset{o}{\sum}\dot{m}{\mathrm{out,}o}\cdot \left( h{\mathrm{out,}o} + \mathrm{g} \cdot z_{\mathrm{out,}o} + \frac{c_{\mathrm{out,}o}^2}{2}\right)\ &- \underset{i}{\sum}\dot{m}{\mathrm{in,}i}\cdot \left( h{\mathrm{in,}i} + \mathrm{g} \cdot z_{\mathrm{in,}i} + \frac{c_{\mathrm{in,}i}^2}{2}\right)-P-\dot{Q} \label{eq:3} \end{split} \[2ex] \begin{split} 0 &=\underset{o}{\sum}\dot{m}{\mathrm{out,}o}\cdot h{\mathrm{out,}o}- \underset{i}{\sum}\dot{m}{\mathrm{in,}i}\cdot h{\mathrm{in,}i}-P-\dot{Q} \label{eq:4} \end{split} \end{align}
The values of heat
- a pipe does not transfer power, thus only heat may be transferred (
$P=0$ ). - turbomachinery is considered adiabatic, thus it only transfers power
(
$\dot{Q}=0$ ).
If chemical reactions take place, the corresponding chemical mass balance is
taken into account instead of equation \ref{eq:2}. On top of that, the energy
balance is different, as the reaction enthalpy has to be considered.
Furthermore, it is necessary to compensate for the different zero point
definitions of enthalpy in the fluid properties of the reaction components by
defining a reference state
\begin{equation} 0= \dot{m}{\mathrm{out}}\cdot\left(h{\mathrm{out}}-h_{\mathrm{out,ref}}\right)- \underset{i}{\sum}\dot{m}{\mathrm{in,}i}\cdot\left(h{\mathrm{in}}- h_{\mathrm{in,ref}}\right){i}- \dot{m}{\mathrm{in}}\cdot\underset{j}{\sum}LHV_{j}\cdot x_{j} \label{eq:5} \end{equation}
With respect to hydraulic state, the pressure drop
\begin{align} 0=p_\mathrm{out}-p_\mathrm{in} + \frac{\rho \cdot c^2 \cdot \lambda\left(\mathrm{Re},k_\mathrm{s},D\right) \cdot L}{2 \cdot D} \label{eq:6}\ 0=pr - \frac{p_\mathrm{out}}{p_\mathrm{in}} \label{eq:7} \end{align}
After designing a specific plant, part-load performance can be determined. For
this, design specific component parameters are calculated in the design case,
for example: the area independent heat transfer coefficient
\begin{equation} 0=\dot{Q}-kA\cdot\Delta\vartheta_\mathrm{log} \label{eq:8} \end{equation}
In general, the design parameters (
The core strength of TESPy lies in the generic and component based architecture allowing to simulate technologically and topologically different thermal engineering applications.
For example, as the increasing share of renewable energy sources to mitigate climate change will result in a significant storage demand, underground gas storage is considered a large scale energy storage option [@IEA; @Pfeiffer]. Due to the feedback regarding the physical parameters of the fluid exchanged between the geological storage and the above-ground plant, an integrated simulation of the storage and the power plant is necessary for a detailed assessment of such storage options [@CAES]. Another important task in energy system transition is renewable heating: Heat pumps using subsurface heat to provide heating on household or even district level show analogous feedback reactions with the underground. As their electricity consumption highly depends on the heat source temperature level, simulator coupling provides valuable assessment possibilities in this field, too. Additionally, TESPy has been coupled with OpenGeoSys [@ogs] for pipeline network simulation of borehole thermal energy storage arrays [@BTES].
This work is supported by University of Applied Sciences and the Center for Sustainable Energy Systems in Flensburg. It is part of the open energy modeling framework (oemof), most known for its software package oemof.solph [@oemof]. Many thanks to all contributors.
Key parts of TESPy require the following scientific software packages: CoolProp [@CoolProp], NumPy [@NumPy], pandas [@pandas]. Other packages implemented are tabulate and SciPy [@SciPy].