Exergy Analysis of a Refrigeration Cycle Python Application Calculator

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Exergy Analysis of a Refrigeration Cycle Python Application Calculator

Exergy Analysis of a Refrigeration Cycle in TESPy Python Application and Calculator

Example for the exergy analysis in TESPy. Find more information about the exergy analysis feature in the respective online documentation.

This is a Python script for calculations of a refrigeration cycle modelthat has the following topology:

refrigeration cycle model

Python code - This application requires knowledge of Python installation and code execution.

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Find the model specifications and results in the refrigeration.py script and the corresponding pdf model report

Valdiation and Results of Exergy Analysis

The tables below show the results of the simulation as well as the validation results. The original data from the publication are provided in the .csv files component_validation.csv and connection_validation.csv .

Connection data

TESPy simulation

e_PH in kJ/kg e_T in kJ/kg e_M in kJ/kg E_PH in kW E_T in kW E_M in kW

0	5.8	5.8	0.0	23.98	23.98	0.00
1	5.8	5.8	0.0	23.98	23.98	0.00
2	163.9	22.1	141.8	674.08	90.85	583.23
3	137.8	0.2	137.6	566.77	0.68	566.09
4	17.1	12.9	4.2	70.28	53.11	17.17
11	2.2	2.2	0.0	22.31	22.31	0.00
12	3.8	3.8	0.0	37.82	37.82	0.00
21	0.1	-0.0	0.1	0.40	-0.00	0.40
22	1.6	1.5	0.1	12.47	12.07	0.40

Absolute difference in the values Δ

Δ m in kg/s Δ T in °C Δ p in bar Δ h in kJ/kg Δ e_T in kJ/kg Δ e_M in kJ/kg

1	-0.085	0.0	0.00	0.0	0.0	0.0
2	-0.085	0.2	0.00	0.1	0.0	-0.0
3	-0.085	-0.0	-0.00	-0.7	0.0	-0.0
4	-0.085	-0.4	0.00	-0.5	0.0	0.0
11	-0.023	0.0	0.00	0.1	0.0	0.0
12	-0.023	0.0	0.00	0.1	0.0	0.0
21	-0.106	0.0	0.00	0.0	-0.0	0.0
22	-0.106	0.0	0.00	-0.0	-0.0	0.0

Relative deviation in the values δ

δ m in % δ T in % δ p in % δ h in % δ e_T in % δ e_M in %

1	-2.024	-0.0	0.0	nan	0.2	nan
2	-2.024	0.1	0.0	0.0	0.5	-0.1
3	-2.024	-0.0	-0.0	-1.0	10.7	-0.0
4	-2.024	0.7	0.0	2.2	1.4	0.1
11	-0.229	-0.0	0.0	0.6	0.2	nan
12	-0.229	-0.0	0.0	0.6	0.1	nan
21	-1.328	0.0	0.0	nan	-inf	0.3
22	-1.328	0.0	0.0	-0.0	-0.3	0.3

Deviation due to differences in fluid property data

Component data

TESPy simulation

E_F in kW E_P in kW E_D in kW ε in % y_Dk in % y*_Dk in %

Cooling heat exchanger	46.30	15.51	30.79	33.5	7.0	7.5
Compressor	815.29	674.08	141.21	82.7	32.1	34.3
Heat sink heat exchanger	107.31	12.07	95.24	11.2	21.7	23.1
Turbine	549.60	404.62	144.98	73.6	33.0	35.2

Disaggregating the Inverter from the Compressor and Turbine

E_F in kW E_P in kW E_D in kW

Compressor	785.21	674.08	111.12
Cooling heat exchanger	46.30	15.51	30.79
Heat sink heat exchanger	107.31	12.07	95.24
Inverter	439.80	395.82	43.98
Turbine	549.60	418.51	131.09

Absolute difference in the values Δ compared to disaggregation

Δ E_F in kW Δ E_P in kW Δ E_D in kW

Compressor	-15.99	-13.82	-2.18
Cooling heat exchanger	-0.26	-0.00	-0.26
Heat sink heat exchanger	-1.79	-0.17	-1.62
Inverter	-7.76	-6.98	-0.78
Turbine	-11.60	-8.79	-2.81

Relative deviation in the values δ compared to disaggregation

δ E_F in % δ E_P in % δ E_D in %

Compressor	-2.00	-2.01	-1.92
Cooling heat exchanger	-0.56	-0.00	-0.84
Heat sink heat exchanger	-1.64	-1.40	-1.67
Inverter	-1.73	-1.73	-1.74
Turbine	-2.07	-2.06	-2.10

High deviation due to differences in component exergy balances

Network data (results only) E_F in kW E_P in kW E_D in kW E_L in kW ε in %

439.80

15.51

412.23

12.07

3.5

Python code - This application requires knowledge of Python installation and code execution.

Support:

Engineers Edge has tested the basic functions and operation of this application using Python 3.11.9 and supporting modules.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Source

The original data of the plant are obtained from the following publication:

T. Morosuk, G. Tsatsaronis, Advanced exergoeconomic analysis of a refrigeration machine: Part 1 — methodology and first evaluation, in: Energy Systems Analysis, Thermodynamics and Sustainability Combustion Science and Engineering Nanoengineering for Energy, Parts A and B, ASMEDC, 2011. doi: 10.1115/imece2011-62688.

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