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Development and optimization of non-geothermal and geothermal-based electricity generation systems in regard to their environmental performance

In the third millennium, developing nations face the most pressing challenges involving climate change, fossil fuel scarcity, ozone depletion, global warming, and the production of greenhouse gases. To mitigate these challenges, renewable energy-driven power generation systems are of paramount importance. Present paper aims at proposal of two novel configurations for clean electricity generation with high-efficiency. The first system (standard system) is composed of an OFWH-assisted steam Rankine cycle and a gas turbine cycle which is driven solely by biomass energy. On the other hand, the second system (hybrid system) uses biomass and geothermal energy to drive the system, where the geothermal energy heats the water entering the OFWH and augments the power generation. Detailed analyses and comparisons between two systems are conducted using thermodynamics and exergoenvironmental methods. After completing the parametric analysis, a Pareto front is obtained for highest efficiency and lowest exergoenvironmental index (EEI). A notable finding of the parametric study is that the hybrid system is less energy efficient than the standard system, however it has higher exergetic efficiency and lower negative impacts on environment. Furthermore, increasing the pressure ratio of the air compressor leads to a consistently increasing EEI, while output electricity and exergy and energy efficiencies show an increasing-decreasing trend. Based on the bi-objective optimization, the gasifier with 3569 kW is the most exergy destructive component of the system in the base case and optimal case. Finally, the optimum values are obtained as 0.4734 and 42.63% for the EEI and exergy efficiency, respectively.
- Universiti Teknologi MARA Malaysia
- Ural Federal University Russian Federation
- Future University in Egypt Egypt
- Khwaja Fareed University of Engineering and Information Technology Pakistan
- King Saud University Saudi Arabia
Parametric study, Environmental assessment, Engineering (General). Civil engineering (General), Pareto front, Geothermal-biomass, Bi-objective optimization, TA1-2040
Parametric study, Environmental assessment, Engineering (General). Civil engineering (General), Pareto front, Geothermal-biomass, Bi-objective optimization, TA1-2040
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