A
considerable amount of thermal energy is available in the form of renewable
energy source and this can reduce the consumption of fossil fuels. The solar
organic rankine cycle is a promising technology which uses energy from the sun
as a source of power and this does not affect the environment. However, due to
the recent global warming, environmental pollution and energy crises coupled
with the instability of oil prices, interest in renewable energy for mitigating
these issues is growing once again. The
aim of this study is to develop a model for evaluating and predicting the net
power output and performance of a solar powered organic rankine cycle and to
validate the model using experimental data.
A thermodynamic analysis was carried out to see how feasible the power plant
will operate on the chosen site, simulation were done in a Matlab environment ,
parametric and sensitivity analysis were also carried out to know the
parameters that effect the system the most. A model was developed to predict
the net power output and thereby performing a performance analysis. The model
was validated using an
experimental setup by Braden Lee Twomey, 2015 at University of Queensland
Australia.
Measured/calculated and
predicted net power output of the solar organic rankine cycle using R134a are
0.905kW, 0.913kW, 0.919kW and 0.908kW, 0.929kW, 0.920kW respectively.
Measured/calculated and predicted net power output of the solar organic rankine
cycle using R245fa are 0.973kW, 0.976kW, 0.979kW and 1.041kW, 0.940kW, 0.953kW
respectively. The organic rankine cycle efficiencies and the overall solar
organic rankine cycle efficiencies using R134a are 0.093, 0.086, 0.077 and
0.000028, 0.000030, 0.000032 respectively.
The organic rankine cycle
efficiencies and the overall solar organic rankine cycle efficiencies using
R245fa are 0.200, 0.185, 0.167 and 0.000060, 0.000065, 0.000069 respectively.
From the above result
it can be deduced that the measured and predicted net power output are close
with very little percentage error and as such the model is able to perform a
performance analysis of the system.
Primary Language | English |
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Subjects | Engineering |
Journal Section | Research Articles |
Authors | |
Publication Date | July 15, 2019 |
Acceptance Date | April 21, 2019 |
Published in Issue | Year 2019 Volume: 1 Issue: 1 |
This work is licensed under a Creative Commons Attribution 4.0 International License