Fossil energy sources have dominated the energy sector for the past century. However, increasing GHG emissions and diminishing fossil fuel reserves expedited implementation of renewable energy conversion processes such as biomass processing and solar power plants. Although these low carbon alternatives will shape the future of energy sector, achieving the CO
2 emission reduction goals will not be possible without the deployment of carbon capture, utilization and storage systems (CCUS) at scale. CCUS systems can be integrated with many processes including natural gas processing, power plants, and biomass conversion. Coal-fired power plants are important due to being the largest emission source, while bioenergy with CCUS (BECCS) is presented as a key for the future of CO
2 mitigation owing to be the only system that has negative net carbon emission. Various synergistic integration options and their theoretical limits should be studied from process systems perspective [1]. For cases of sustainable biomass, to have a reasonable yield, biomass conversion should be augmented by a carbon-free energy source [2]. Recently proposed hydricity process is an example to supply H
2, from solar thermal energy [3]. For the case of energy crops, growing biomass is not the most efficient use of limited land area [4]. To determine the potential of different alternatives we have created a process superstructure (PS) of conversion processes and CCUS technologies. PS includes coal-fired power plants, biomass conversion processes such as gasification and pyrolysis; upgrading processes such as FT and methane production; power generation options such as combined and steam cycles. PS also includes various CCUS systems such as pre-, post- and oxy-combustion, CO
2-conversion and storage options. Simulations and optimization of the proposed PS are performed using an integrated Matlab and Aspen platform [5]. The operating conditions and topological structure of the integrated process are determined via sensitivity analysis and optimization using genetic algorithm in Matlab. The PS is used for techno-economic assessment for integration of various biomass conversion processes and CCUS technologies. The study provides synergistic process designs that maximize energetic and economic performance. The promising integrations, preferred application areas and the details of modeling approach are presented.
1 Gençer E, Agrawal R. Strategy to synthesize integrated solar energy coproduction processes with optimal process intensification. Case study: Efficient solar thermal hydrogen production. Computers & Chemical Engineering, 2017. Doi: 10.1016/j.compchemeng.2017.01.038.
2 Mallapragada DS, Tawarmalani M, Agrawal R. Synthesis of augmented biofuel processes using solar energy. AIChE J., 60(7), 2533-2545, 2014.
3 Gençer E, Mallapragada DS, Marechal F, Tawarmalani M, Agrawal R, Round-the-clock power supply and a sustainable economy via synergistic integration of solar thermal power and hydrogen processes. PNAS, 112 (52), 15821-15826, 2015.
4 Mallapragada DS, Singh N, Curteanu V, Agrawal R, Sun-to-fuel assessment of routes for fixing CO2 as liquid fuel, I&EC, 52(14), 5136-5144, 2013.
5 Gençer E, Tawarmalani M, Agrawal R, Integrated solar thermal hydrogen and power coproduction process for continuous power supply and production of chemicals, CACE, 37, 2291-2296, 2015.
