OPTIMAL DESIGN OF ORGANIC RANKINE CYCLE POWER PLANTS FOR EFFICIENT UTILIZATION of BIOMASS ENERGY IN NIGERIA

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.

Keywords

• Organic Rankine Cycle
• Biomass Energy
• Renewable Power Plant
• Sustainable Energy System
• ORC Thermodynamic Optimization

Thanks

The authors gratefully acknowledge the reviewers for their scientific contributions to this article.

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