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contributor authorRossi, Iacopo
contributor authorZaccaria, Valentina
contributor authorTraverso, Alberto
date accessioned2019-02-28T10:58:16Z
date available2019-02-28T10:58:16Z
date copyright1/10/2018 12:00:00 AM
date issued2018
identifier issn0742-4795
identifier othergtp_140_05_051703.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4251290
description abstractThe use of model predictive control (MPC) in advanced power systems can be advantageous in controlling highly coupled variables and optimizing system operations. Solid oxide fuel cell/gas turbine (SOFC/GT) hybrids are an example where advanced control techniques can be effectively applied. For example, to manage load distribution among several identical generation units characterized by different temperature distributions due to different degradation paths of the fuel cell stacks. When implementing an MPC, a critical aspect is the trade-off between model accuracy and simplicity, the latter related to a fast computational time. In this work, a hybrid physical and numerical approach was used to reduce the number of states necessary to describe such complex target system. The reduced number of states in the model and the simple framework allow real-time performance and potential extension to a wide range of power plants for industrial application, at the expense of accuracy losses, discussed in the paper.
publisherThe American Society of Mechanical Engineers (ASME)
titleAdvanced Control for Clusters of SOFC/Gas Turbine Hybrid Systems
typeJournal Paper
journal volume140
journal issue5
journal titleJournal of Engineering for Gas Turbines and Power
identifier doi10.1115/1.4038321
journal fristpage51703
journal lastpage051703-8
treeJournal of Engineering for Gas Turbines and Power:;2018:;volume( 140 ):;issue: 005
contenttypeFulltext


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