Optimal operational adjustment in multi-functional energy systems in response to process inoperability

Multi-functional energy systems such as biorefineries and polygeneration plants are able to efficiently produce product portfolios by taking advantage of inherent opportunities for optimal integration among process units. Thus, such systems provide valuable solutions towards efficient, sustainable a...

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Bibliographic Details
Main Authors: Kasivisvanathan, Harresh, Barilea, Ivan Dale U., Ng, Denny K.S., Tan, Raymond Girard R.
Format: text
Published: Animo Repository 2013
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/2315
https://animorepository.dlsu.edu.ph/context/faculty_research/article/3314/type/native/viewcontent
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Institution: De La Salle University
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Summary:Multi-functional energy systems such as biorefineries and polygeneration plants are able to efficiently produce product portfolios by taking advantage of inherent opportunities for optimal integration among process units. Thus, such systems provide valuable solutions towards efficient, sustainable and economically viable production of energy, fuels, utilities and commodity chemicals. On the other hand, the high level of interdependency among process units within such industrial plants is also a potential disadvantage, since the inoperability of one process unit propagates upstream and downstream through the process network to affect other operations. This paper presents a simple mixed-integer linear programming (MILP) model for determining optimal process adjustments in multi-functional energy systems as a result of partial inoperability. The methodology assumes that partial or complete inoperability of some of the process units within the plant forces it to operate away from the baseline state that it was originally designed for. For example, such emergency conditions may result from damaged process equipment. The MILP model determines the optimal reallocation of process streams and operating levels of the process units in order to maximise operating profits from the product portfolio. © 2012 Elsevier Ltd.