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OPTIMAL DESIGN OF ORGANIC RANKINE CYCLE POWER PLANTS FOR EFFICIENT UTILIZATION of BIOMASS ENERGY IN NIGERIA
2023
Journal:  
Journal of Scientific Reports-A
Author:  
Abstract:

This study investigated the optimal design choice among four organic Rankine cycle (ORC) configurations for efficient utilization of solid biomass energy in Nigeria. Although vast opportunities exist for large-scale biomass power plants in the country, there has been little or no practical implementation yet, due to the limitation of technical know-how regarding thermodynamic conversion technologies. To bridge this gap, a thermodynamic optimization technique was applied in this study to the ORC. Specifically, the subcritical ORC (SUBORC), the regenerative subcritical ORC (SUBORC-REGEN), the supercritical ORC (SUPERORC), and the regenerative supercritical ORC (SUPERORC-REGEN) configurations were compared using established zero-dimensional optimization models implemented in MATLAB. Results showed that the SUPERORC-REGEN would be the most preferred choice amongst the options compared. Specifically, a palm kernel expeller (PKE) biomass fuel considered could yield about 1.98 MW of power at a thermal efficiency of about 28%. Additionally, it was obtained that the supercritical ORC would always outperform the subcritical types technically, with or without a regenerator. For the regenerative configurations, results showed that the supercritical ORC would generate 113 kW and 429 kW more net power than the subcritical ORC, respectively for n-pentane and n-butane working fluids. Similarly, the study reiterated that adopting a regenerative configuration would improve ORC performance. For instance, the SUPERORC-REGEN yielded 63% and 73% more power than the SUPERORC, respectively for n-pentane and n-butane working fluids. The practical economic implications of the different ORC configurations should be examined in future studies, alongside the investigation of exergy-based optimization potentials on component basis.

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2023
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Journal of Scientific Reports-A

Field :   Fen Bilimleri ve Matematik; Mühendislik

Journal Type :   Ulusal

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Article : 764
Cite : 1.290
2023 Impact : 0.117
Journal of Scientific Reports-A