Forward-Checking Filtering for Nested Cardinality Constraints: Application to an Energy Cost-Aware Production Planning Problem for Tissue Manufacturing

Dejemeppe, Cyrille; Devolder, Olivier; Lecomte, Victor; Schaus, Pierre

doi:10.1007/978-3-319-33954-2_9

Cited by 2 publications

(2 citation statements)

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“…• other flexibility levers can be available, such as load shifting or scheduling, depending on the exact process, with varying degrees of impact on the production and the consumption. The paper industry falls into this category, with production plan reordering [10].…”

Section: Introductionmentioning

confidence: 99%

“…For example, in aluminium smelting, any reduction of the current fed into the electrolysis potlines implies a loss of production (Todd et al, 2008); -other flexibility levers can be available, such as load shifting or scheduling, depending on the exact process, with varying degrees of impact on the production and the consumption. The paper industry falls in this category, with production plan reordering (Dejemeppe et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Embedding reservoirs in industrial models to exploit their flexibility

Cuvelier

2020

SN Appl. Sci.

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In the context of energy transition, industrial plants that heavily rely on electricity face more and more price volatility. To continue operating in these conditions, the directors become continually more willing to increase their flexibility, i.e. their ability to react to price fluctuations. This work proposes an intuitive methodology to mathematically model electro-intensive processes in order to assess their flexibility potential. To this end, we introduce the notion of reservoir, a storage of either material or energy, that allows models based on this paradigm to have interpretations close to the physics of the processes. The design of the reservoir methodology has three distinct goals: (i) to be easy and quick to build by an energy-sector consultant; (ii) to be effortlessly converted into mixed-integer linear or nonlinear programs; (iii) to be straightforward to understand by nontechnical people, thanks to their graphic nature. We apply this methodology to two industrial case studies, namely an induction furnace (linear model) and an industrial cooling installation (nonlinear model), where we can achieve significant cost savings. In both cases, the models can be quickly written using our method and solved by appropriate solver technologies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%