Advances in mathematical programming models for enterprise-wide optimization

Grossmann, Ignacio E.

doi:10.1016/j.compchemeng.2012.06.038

Cited by 187 publications

(85 citation statements)

References 123 publications

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“…Other approaches involving decomposition methods as Bender, Lagrangian, bi-level or rolling horizon decompositions can be used to reduce the computational time of problems with numerous variables, as described in Grossmann (2012). Rolling horizon (RH) approach allows to solve a large size problem by breaking it down in multiple smaller ones solved iteratively Dimitriadis et al (1997).…”

Section: Research In Energy Optimisationmentioning

confidence: 99%

A holarchic approach for multi-scale distributed energy system optimisation

et al. 2017

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The benefits of decentralized energy systems can be realised through the optimal siting of distributed energy systems and the design of highly interlinked district heating networks within existing electrical and gas networks. The problem is often formulated as a Mixed Integer Linear Programming (MILP) problem. MILP formulations are efficient and reliable, however the computational burden increases drastically with the number of integer variables, making detailed optimisation infeasible at large urban scales. To tackle complex problems at large scale the development of an efficient and robust simplification method is required. This paper presents an aggregation schema to facilitate the optimisation of urban energy systems at city scale.Currently, spatial and/or temporal aggregation are commonly employed when modelling energy systems at spatiotemporal resolutions from plant scheduling up to national scenarios. This paper argues for solving different scales separately using a bottom-up approach, while keeping track of the error made by reducing the resolution when moving from building to urban scale. Novel modelling formulations and optimisation techniques are presented. They enable drastic reduction of the computational time (by up to a factor of 100) required to find an optimal solution in reasonable time without sacrificing the quality of the results (no more than 1% loss in accuracy).A density-based clustering algorithm enables intelligent division of a large city-scale problem into sub-optimisation problems by creating clusters of different density. In each cluster, the trade-off between centralized and decentralized energy systems and the associated district heating network design is evaluated. A solution is selected based on a local optimisation of the network costs. Demand profiles of each building are assigned appropriately, then at an upper level the energy optimisation problem is solved considering the network losses at lower levels. This method enables large-scale modelling of urban energy systems while taking into account building-scale levels of detail. The clustering method enables assessment of the potential of district heating networks on city scale based on building characteristics and available urban energy systems.

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Section: Research In Energy Optimisationmentioning

confidence: 99%

A holarchic approach for multi-scale distributed energy system optimisation

et al. 2017

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“…Integrated decision-making as a means for efficient use of data and knowledge has been highlighted in the "National Strategic Plan for Advanced Manufacturing" published by the Executive Office of the President in 2012. Enterprise-wide decision-making demands the integration of operational activities of planning, scheduling, and control [8]. Control of unit operations needs mechanistic models.…”

Section: The Importance Of Reliable Unit Operation Modelsmentioning

confidence: 99%

A Framework for the Development of Integrated and Computationally Feasible Models of Large-Scale Mammalian Cell Bioreactors

Farzan

Ierapetritou

2018

Processes

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Industrialization of bioreactors has been achieved by applying several core concepts of science and engineering. Modeling has deepened the understanding of biological and physical phenomena. In this paper, the state of existing cell culture models is summarized. A framework for development of dynamic and computationally feasible models that capture the interactions of hydrodynamics and cellular activities is proposed. Operating conditions are described by impeller rotation speed, gas sparging flowrate, and liquid fill level. A set of admissible operating states is defined over discretized process parameters. The burden on a dynamic solver is reduced by assuming hydrodynamics at its fully developed state and implementation of compartmental modeling. A change in the conditions of operation is followed by hydrodynamics switching instantaneously to the steady state that would be reached under new conditions. Finally, coupling the model with optimization solvers leads to improvements in operation.

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“…An extensive review is provided in Grossmann and Furman (2009). The topic of integration of planning and scheduling with control, on the other hand, is a topic that still has not received much attention in the literature (Grossmann (2012); Craig et al (2011)). This topic is also viewed differently by different authors, mainly because of different interpretations of the area of control, which can be said to work in timescales of both milliseconds, minutes and hours.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Scheduling and Utility Disturbance Management in the Process Industry

Lindholm

Johnsson

Quttineh

et al. 2013

IFAC Proceedings Volumes

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Management, and Control, 2013 (pp. 140-145). IFAC. DOI: 10.3182/20130619-3-RU-3018.00106 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract: The integration of scheduling and control in the process industry is a topic that has been frequently discussed during the recent years, but many challenges remain in order to achieve integrated solutions that can be implemented for large-scale industrial sites. In this paper we consider production control under disturbances in the supply of utilities at integrated sites together with the integration towards production scheduling. Utilities, such as steam and cooling water, are often shared between the production areas of a site, which enables formulation of an optimization problem for determining the optimal supply of utilities to each area at the occurrence of a disturbance. Optimization in two timescales is suggested to handle the scheduling and disturbance management problems in a hierarchical fashion. The suggested structure has been discussed with companies within the chemical process industry. A simple example is provided to show how the structure may be used.

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Advances in mathematical programming models for enterprise-wide optimization

Cited by 187 publications

References 123 publications

A holarchic approach for multi-scale distributed energy system optimisation

A holarchic approach for multi-scale distributed energy system optimisation

A Framework for the Development of Integrated and Computationally Feasible Models of Large-Scale Mammalian Cell Bioreactors

Hierarchical Scheduling and Utility Disturbance Management in the Process Industry

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