Abstract
Based on the benefits of integrated gasification combined cycles (IGCCs), a cogeneration plant for providing electricity and freshwater is proposed. The main novelties of the devised system are the integration of biomass gasification and a regenerative gas turbine with intercooling and a syngas combustor, where the syngas produced in the gasifier is burned in the combustion chamber and fed to a gas turbine directly. The energy discharged from the gas turbine is utilized for further electricity and freshwater generation via Kalina and MED hybridization. The proposed system is analyzed from energy, exergy, exergoeconomic, and reliability–availability viewpoints. The optimal operating condition and optimum performance criteria are obtained by hybridizing an artificial neural network (ANN), the multi-objective particle swarm optimization (MOPSO) algorithm. According to results obtained, for the fourth scenario of the optimization process, optimal values of 45.10%, 14.27 kg·s−1, 12.95 USD·GJ−1, and 8141 kW are obtained for the exergy efficiency, freshwater production rate, sum unit cost of products, and net output power, respectively. According to reliability and availability assessment, the probability of the healthy working state of all components and subsystems is 88.4403%; the system is shown to be 87.74% available of the time over the 20-year lifetime.
Highlights
Considerable reduction in fossil fuel resources, greenhouse gases emission, and environmental issues, such as global warming and acid rain, prompted the researchers to explore carbon-free and more environmentally benign energy sources [1]
The energy discharged from the gas turbine is utilized through a Heat recovery steam generator (HRSG) for further electricity and freshwater generation. Another key motivation of the proposed system is the combination of a steam Rankine cycle (SRC) and a multieffect distillation (MED) desalination unit, where the latter device acts as the condenser in the SRC plant
To ensure the validity of the results obtained from the modeling process in Engineering Equation Solver (EES) software, it is necessary to measure the validity of the model with previously published independent research or with experimental data
Summary
Considerable reduction in fossil fuel resources, greenhouse gases (carbon dioxide, Sulfur dioxide, and nitrogen oxide) emission, and environmental issues, such as global warming and acid rain, prompted the researchers to explore carbon-free and more environmentally benign energy sources [1]. A combined system consisting of a multi-stage flash (MSF) desalination unit, a gas turbine (GT), and an HRSG unit was studied by Hosseini et al [25] from thermodynamic and reliability viewpoints They determined that the application of reliability analysis could increase the water and electricity generation costs by about 6.40% and 4.10%, respectively. Wang et al [27] developed a modified exergoeconomic analysis considering space-state reliability assessment to study the cost assignations in a biomass-based multi-generation plant Their results revealed that the gasification system’s repair and failure rates considerably affect the product cost. The energy discharged from the gas turbine is utilized through a HRSG for further electricity and freshwater generation Another key motivation of the proposed system is the combination of a SRC and a MED desalination unit, where the latter device acts as the condenser in the SRC plant. A multi-objective optimization is carried out to determine the optimum values of the main design parameters and objective functions using an artificial neural network (ANN), with MOPSO as the optimization algorithm and the TOPSIS method as the decision-maker
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