4.6 Article

Flexible operation of coal fired power plant integrated with post combustion CO2 capture using model predictive control

期刊

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ijggc.2018.12.004

关键词

Coal-fired power plant; Solvent-based post-combustion carbon capture; Model predictive control; Dynamic behavior analysis; Flexible operation

资金

  1. National Natural Science Foundation of China (NSFC) [51506029]
  2. Natural Science Foundation of Jiangsu Province, China [BK20150631]
  3. China Postdoctoral Science Foundation
  4. Jiangsu Province Postdoctoral Science Foundation
  5. EU [PIRSES-GA-2013-612230]
  6. Royal Society-Sino British Fellowship Trust International Fellowship

向作者/读者索取更多资源

The growing demand for CO2 capture from coal-fired power plant (CFPP) has increased the need to improve the dynamic operability of the integrated power generation-CO2 capture plant. Nevertheless, high-level operation of the entire system is difficult to achieve due to the strong interactions between the CFPP and post combustion CO2 capture (PCC) unit. In addition, the control tasks of power generation and CO2 removal are in conflict, since the operation of both processes requires consuming large amount of steam. For these reasons, this paper develops a model for the integrated CFPP-PCC process and analyzes the dynamic relationships for the key variables within the integrated system. Based on the investigation, a centralized model predictive controller is developed to unify the power generation and PCC processes together, involving the key variables of the two systems and the interactions between them. Three operating modes are then studied for the predictive control system with different focuses on the overall system operation; power generation demand tracking and satisfying the CO2 capture requirement. The predictive controller can achieve a flexible operation of the integrated CFPP-PCC system and fully exert its functions in power generation and CO2 reduction.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据