文献类型：期刊文献

英文题名：Intelligent scheduling and flexible operation for the commercial-scale coal-fired power plant integrated with post-combustion carbon capture

作者：Liao, Peizhi[1]; Wu, Xiao[2]; Wang, Meihong[1]

机构：[1] Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, School of Information Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China; [2] Key Laboratory of Energy Thermal Conversion and Control, Ministry of Education, School of Energy and Environment, Southeast University, Nanjing, 210096, China

年份：2022

卷号：55

期号：9

起止页码：553

外文期刊名：IFAC-PapersOnLine

收录：EI(收录号：20223612697803)

语种：英文

外文关键词：Carbon capture - Coal - Coal combustion - Coal fired power plant - Coal fueled furnaces - Fossil fuel power plants - Mining - Predictive control systems

摘要：This paper develops a two-level control structure for commercial-scale coal-fired power plant integrated with post-combustion carbon capture (CFPP-PCC). In high-level scheduler, an economic objective function with the consideration of grid demand, price conditions and system constraints is developed. Deep belief network is utilized to develop the steady-state model for CFPP-PCC process. Intelligent scheduling of electricity generation and capture level is then implemented using Bayesian optimization. Given the optimal setpoints, model predictive controller (MPC) is applied to achieve flexible operation in the low-level supervisory control. The simulation results show that the proposed control structure specifies an economically attractive operation profile for the CFPP-PCC process. ? 2022 Elsevier B.V.. All rights reserved.