International Journal of Engineering and Innovative Research
Yazarlar: Eghosa OMO-OGHOGHO, Sufianu ALİU
Konular:Mühendislik
Anahtar Kelimeler:Solar organic rankine,Thermal energy,Net power output,Efficiency
Özet: 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.