文章基本信息

标题：Optimal Control of Combined-Cycle Power Plants: A Data-Enabled Predictive Control Perspective
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作者：Pouya Mahdavipour ; Christoph Wieland ; Hartmut Spliethoff 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2022
卷号：55
期号：13
页码：91-96
DOI：10.1016/j.ifacol.2022.07.241
语种：English
出版社：Elsevier
摘要：AbstractIn this work, we propose an optimal control strategy as the unit control for combined-cycle power generation units. Using the same optimal control, we propose to optimize other internal control structures. Data-Enabled Predictive Control is chosen as the optimal control problem formulation, as it does not require a parametric state-space representation of the system. This bypasses the challenging and expensive-to-solve issue of parametric modeling and linearization for highly nonlinear systems. The performance of the controller is investigated in several critical operational scenarios, such as load-following for frequency control and disturbance rejection. Simulation results in Apros®, which is an environment dedicated to advanced process simulation, are presented.
关键词：KeywordsData-Enabled Predictive ControlPower NetworksFlexibilityPower Plant ControlFrequency ControlLoad Cycling