Scheduling and energy – Industrial challenges and opportunities

Merkert, Lennart; Harjunkoski, Iiro; Isaksson, Alf; Säynevirta, Simo; Saarela, Antti; Sand, Guido

doi:10.1016/j.compchemeng.2014.05.024

Cited by 147 publications

(80 citation statements)

References 54 publications

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“…In the spirit of industrial Demand Side Management (Samad and Kiliccote, 2012;Merkert et al, 2014), we develop a scheduling model to assess the potential benefits of an integrated ASU-CES plant. In the proposed framework, robust optimization techniques are applied to model the uncertainty in operating reserve demand.…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling of Air Separation with Cryogenic Energy Storage

Zhang

Heuberger

Grossmann

et al. 2015

12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering

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Section: Introductionmentioning

confidence: 99%

Optimal Scheduling of Air Separation with Cryogenic Energy Storage

Zhang

Heuberger

Grossmann

et al. 2015

12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering

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“…• Assess models' solution time and prove its robustness as a decision-maker in rapidly changing market scenarios, as stated by Merkert et al [27].…”

Section: Framework and Mathematical Model Formulationmentioning

confidence: 99%

“…According to Merkert et al [27], MILP is a technology that can address operational issues related to energy. According to this author, the technique has evolved over the past two decades and today it can solve a wide range of problems based on reduction by a factor of a million in solution time.…”

Section: Enterprise-wide Optimizationmentioning

confidence: 99%

Enterprise-wide optimization in a petrochemical plant: a MILP approach to energy efficiency improvement

2017

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Public policy, dollar rate, market prices, contracts values and equipment efficiency influence the costs of the energy sources at an ethylene plant. The aim of this research is to identify energy efficiency opportunities at the energy management resources in a petrochemical industry. It was proved that using MILP makes it possible to achieve energy efficiency gains. MILP proved to be effective, accurate and robust. It confirmed the importance of modeling and simulation with quick response and its implementation in a higher possible rate, since the potential gains running the model once per day were 81% higher than performing it once a month. The optimal resources choice had an average annual potential saving of US$ 556.000/year.

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“…From an economic perspective, energy-efficient production scheduling reduces the energy cost, under a volatile energy price from the deregulated electricity markets (Merkert et al, 2015). For many power-intensive industries, the electricity cost accounts for 10-50% of the final product cost (Hadera and Harjunkoski, 2013).…”

Section: Introductionmentioning

confidence: 99%

Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: An empirical study

Gong

Wee

Pessemier

et al. 2017

Journal of Cleaner Production

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With the penetration of smart grid into factories, energyefficient production scheduling has been emerged. It shifts flexible production loads to lower-priced periods to reduce energy cost for the same production task. However, the existing methods only focus on integrating energy awareness to conventional production scheduling models. They ignore the labor cost which is shift-based and follows an opposite trend of energy cost. For instance, the energy cost is lower during nights while the labor cost is higher. Therefore, this paper proposes a method for energy-efficient and labor-aware production scheduling at the unit process level. This integrated scheduling model is mathematically formulated. Besides the state-based energy model and genetic algorithm-based optimization, a continuous-time shift accumulation heuristic is proposed to synchronize power states and labor shifts. In a case study of a Belgian plastic bottle manufacturer, a set of empirical sensitivity analyses were performed to investigate the impact of energy and labor awareness, as well as the production-related factors that influence the economic performance of a schedule. Furthermore, the demonstration was performed in 9 large-scale test instances, which encompass the cases where energy cost is minor, medium, and major compared to the joint energy and labor cost. The results have proven that the ignorance of labor in existing energy-efficient production scheduling studies increases the joint energy and labor cost, although the energy cost can be minimized. To achieve effective production cost reduction, energy and labor awareness are recommended to be jointly considered in production scheduling. 1Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: an empirical study AbstractWith the penetration of smart grid into factories, energy-efficient production scheduling has been emerged. It shifts flexible production loads to lower-priced periods to reduce energy cost for the same production task. However, the existing methods only focus on integrating energy awareness to conventional production scheduling models. They ignore the labor cost which is shift-based and follows an opposite trend of energy cost. For instance, the energy cost is lower during nights while the labor cost is higher. Therefore, this paper proposes a method for energy-efficient and laboraware production scheduling at the unit process level. This integrated scheduling model is mathematically formulated. Besides the state-based energy model and genetic algorithm-based optimization, a continuous-time shift accumulation heuristic is proposed to synchronize power states and labor shifts. In a case study of a Belgian plastic bottle manufacturer, a set of empirical sensitivity analyses were performed to investigate the impact of energy and labor awareness, as well as the production-related factors that influence the economic performance of a schedule. Furthermore, the demonstration was performed in 9 large-scale test instan...

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Scheduling and energy – Industrial challenges and opportunities

Cited by 147 publications

References 54 publications

Optimal Scheduling of Air Separation with Cryogenic Energy Storage

Optimal Scheduling of Air Separation with Cryogenic Energy Storage

Enterprise-wide optimization in a petrochemical plant: a MILP approach to energy efficiency improvement

Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: An empirical study

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