Agile control of CO₂ capture technology for maximum net operating revenue

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• 作者：Norhuda Abdul Manaf ^{nabd3370@uni.sydney.edu.au" class="auth_mail" title="E-mail the corresponding author} ; Abdul Qadir ^{abdul.qadir@sydney.edu.au" class="auth_mail" title="E-mail the corresponding author} ; Ali Abbas ^{ali.abbas@sydney.edu.au" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Algorithm ; Automatic control (close-loop engineering) ; Optimization devices ; Plant wide ; Multi-input multi-output system ; Nonlinear system
• 刊名：IFAC-PapersOnLine
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：49
• 期：7
• 页码：332-335
• 全文大小：2615 K

文摘

This paper uses a multi-layered control scheme consisting of model predictive control (MPC) and mixed integer non-linear programming (MINLP) for the analysis of power plant net operating revenue when retrofitted with a post-combustion carbon capture (PCC) plant. The capability of the proposed control scheme is examined for 24-hour operations of an integrated plant (power plant with PCC) in the years 2011 and 2020. The control scheme is tested in response to variability in upstream power plant dynamic loads. The agility of the control scheme subject to forecast 2020 electricity and carbon prices is shown to result in yearly net operating revenue of approximately 12% of the gross revenue. Whereas, the same integrated plant generates a net operating revenue loss of roughly 13% of the gross revenue under 2011 electricity and carbon prices.