Integrating low steam demand CO shift process to coal based polygeneration energy systems: Process design and analysis
He, Fen; Liu, Pei; Li, Z; Ni, W
| HERO ID | 1447264 |
|---|---|
| In Press | No |
| Year | 2012 |
| Title | Integrating low steam demand CO shift process to coal based polygeneration energy systems: Process design and analysis |
| Authors | He, Fen; Liu, Pei; Li, Z; Ni, W |
| Journal | Energy |
| Volume | 45 |
| Issue | 1 (Sep 1 |
| Page Numbers | 169-175 |
| Abstract | Coal based polygeneration, a technology that couples power generation and chemical production, is a promising solution to the challenges of fossil fuel depletion and greenhouse gas emissions. Carbon monoxide shift process is a key unit in polygeneration, which adjusts hydrogen and CO ratio according to the requirements of downstream processes. Usually steam is added to shift the gas composition extensively, which contributes considerably to the energy efficiency penalty. This paper presents a polygeneration system with a low steam demand CO shift process, based on a recently developed catalyst QDB-04. Compared with a conventional CO shift, the proposed process is characterized by a low steam to CO ratio in the feeding syngas, and the steam required for the CO shift can be significantly reduced. A model of the proposed CO shift process was developed and its performance was compared with a conventional CO shift. Key system parameters were chosen to integrate the low steam CO shift process in a methanol/power polygeneration system. Based on flowsheet simulation, an energy assessment was performed to compare the proposed polygeneration system with a conventional one. Results show that the polygeneration with the low steam CO shift process has considerable energy savings over the conventional scheme. |
| Doi | 10.1016/j.energy.2012.01.043 |
| Wosid | WOS:000309243700020 |
| Is Certified Translation | No |
| Dupe Override | No |
| Comments | Source: Web of Science WOS:000309243700020 |
| Is Public | Yes |
| Keyword | Steam electric power generation; Air pollution; Mathematical models; Marketing; Coal; Methyl alcohol; Carbon monoxide; Gas composition; 2012) |