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Records with Keyword: Polygeneration
Simulation of Polygeneration Systems
Francesco Calise, Massimo Dentice D’Accadia
February 5, 2019 (v1)
Keywords: distributed generation, dynamic simulations, Polygeneration, Renewable and Sustainable Energy
This Special Issue aims at collecting the recent studies dealing with polygeneration systems, with a special focus on the possible integration of different technologies into a single system, able to convert one or multiple energy sources into energy services (electricity, heat and cooling) and other useful products (e.g., desalinized water, hydrogen, glycerin, ammonia, etc.). Renewable sources (solar, wind, hydro, biomass and geothermal), as well as fossil fuels, feeding advanced energy systems such as fuel cells and cogeneration systems, are considered. Special attention is paid to control strategies and to the management of the systems in general. Studies including thermoeconomic analyses and system optimizations are presented.
Combining Biomass, Natural Gas, Carbonless Heat to produce liquid fuels
Leila Hoseinzade, Thomas A Adams II
August 15, 2018 (v1)
Keywords: Biomass, Carbonless Heat, Natural Gas, Polygeneration
In this study, a new Biomass-Gas-Nuclear heat-To-Liquid fuel (BGNTL) process is presented which uses high-temperature nuclear heat as the heat source for steam methane reforming (SMR). This process co-produces liquid fuels (Fischer-Tropsch liquids, methanol and DME) and power. The BGNTL process was simulated using a combination of different software packages including gPROMS, MATLAB, ProMax, and Aspen Plus. This included the use of a rigorous multi-scale model for the nuclear-heat-powered SMR reactor which was developed in a prior work in gPROMS. Energy efficiency and cradle-to-grave life cycle inventory and life-cycle impact analyses of greenhouse gas (GHG) emissions were accomplished to analyze the environmental impacts of the BGNTL system. Plant performance was compared with a base case Biomass-Gas-To-Liquid (BGTL) process at the same size. In both processes, a carbon capture and storage (CCS) option is considered. It has been found that both processes result in negative total life... [more]
Biomass-Gas-and-Nuclear-To-Liquids (BGNTL) Processes Part I: Model Development and Simulation
James Alexander Scott, Thomas Alan Adams II
August 7, 2018 (v1)
New polygeneration processes for the co-production of liquid fuels (Fischer-Tropsch liquids, methanol, and dimethyl ether) and electricity are presented. The processes use a combination of biomass, natural gas, and nuclear energy as primary energy feeds. Chemical process models were created and used to simulate candidate versions of the process, using combinations of models ranging from complex multi- scale models to standard process flowsheet models. The simulation results are presented for an Ontario, Canada case study to obtain key metrics such as efficiency and product conversions. Sample Aspen Plus files are provided in the supplementary material to be used by others.
The Optimal Design of a Distillation System for the Flexible Polygeneration of Dimethyl Ether and Methanol Under Uncertainty
Thomas A. Adams II, Tokiso Thatho, Matthew C. Le Feuvre, Christopher L.E. Swartz
June 12, 2018 (v1)
Two process designs for the separation section of a flexible dimethyl ether and methanol polygeneration plant are presented, as well as an optimization method which can determine the optimal design under market uncertainty quickly and to global optimality without loss of model fidelity. The polygeneration plant produces a product mixture that is either mostly dimethyl ether or mostly methanol depending on market conditions by using a classic two-stage dimethyl ether production catalytic reaction route in which the second stage is bypassed when the market demand is such that methanol production is more favorable than dimethyl ether. The downstream distillation sequence is designed to purify the products to desired specifications despite the wide variability in feed condition that corresponds to the upstream reaction system operating either in DME-rich or methanol-rich mode. Because the optimal design depends on uncertain market conditions (realized as the percentage of the time in which... [more]
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