Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach
Considering economic and environmental concerns as well as thermal and visual comfort requirements, this paper introduces the idea of Smart Energy-Aware Manufacturing Plant Scheduling for general manufacturing processes, especially high-value-added ones. The integrated system benefits from the use o...
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| Vydáno v: | Energy (Oxford) Ročník 209; s. 118385 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Oxford
Elsevier Ltd
15.10.2020
Elsevier BV |
| Témata: | |
| ISSN: | 0360-5442, 1873-6785 |
| On-line přístup: | Získat plný text |
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| Abstract | Considering economic and environmental concerns as well as thermal and visual comfort requirements, this paper introduces the idea of Smart Energy-Aware Manufacturing Plant Scheduling for general manufacturing processes, especially high-value-added ones. The integrated system benefits from the use of a grid-connected Microgrid, a combined cooling, heat, and power system, and renewable power. Employing the Conditional Value-at-Risk and guaranteeing both solution and model robustness through an original multi-objective risk-based robust mixed-integer linear programming to optimally support the system make the contribution of the paper novel and unique. The main objective is to schedule manufacturing (non-shiftable) and non-manufacturing (shiftable and interruptible) loads, and distributed energy resources based on the real-time-pricing policy in an interactive decentralized operation of a capacitated multi-carrier energy production-consumption system. Compared to the conventional system, the results outline 64.63%, 1.62%, 100%, and 65.23% less Carbon dioxide emissions, net production, power exchange, and total costs, on average. The proposed framework is preferable to the framework that is based on the use of combined heat and power systems, at least in terms of a reduction in production costs. Considering both the supply- and demand-side uncertainties, the framework performs good trade-offs between solution robustness and model robustness, and environmental and economic concerns.
•Introducing the idea of Smart Energy-Aware Manufacturing Plant Scheduling.•Proposing a new multi-objective risk-based robust Mixed Integer Linear Programming.•Obtaining 64.63%, 1.62%, and 65.23% less emission, production, and total costs.•Providing a good trade-off between solution and model robustness.•Providing a constructive trade-off between environmental and economic concerns. |
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| AbstractList | Considering economic and environmental concerns as well as thermal and visual comfort requirements, this paper introduces the idea of Smart Energy-Aware Manufacturing Plant Scheduling for general manufacturing processes, especially high-value-added ones. The integrated system benefits from the use of a grid-connected Microgrid, a combined cooling, heat, and power system, and renewable power. Employing the Conditional Value-at-Risk and guaranteeing both solution and model robustness through an original multi-objective risk-based robust mixed-integer linear programming to optimally support the system make the contribution of the paper novel and unique. The main objective is to schedule manufacturing (non-shiftable) and non-manufacturing (shiftable and interruptible) loads, and distributed energy resources based on the real-time-pricing policy in an interactive decentralized operation of a capacitated multi-carrier energy production-consumption system. Compared to the conventional system, the results outline 64.63%, 1.62%, 100%, and 65.23% less Carbon dioxide emissions, net production, power exchange, and total costs, on average. The proposed framework is preferable to the framework that is based on the use of combined heat and power systems, at least in terms of a reduction in production costs. Considering both the supply- and demand-side uncertainties, the framework performs good trade-offs between solution robustness and model robustness, and environmental and economic concerns. Considering economic and environmental concerns as well as thermal and visual comfort requirements, this paper introduces the idea of Smart Energy-Aware Manufacturing Plant Scheduling for general manufacturing processes, especially high-value-added ones. The integrated system benefits from the use of a grid-connected Microgrid, a combined cooling, heat, and power system, and renewable power. Employing the Conditional Value-at-Risk and guaranteeing both solution and model robustness through an original multi-objective risk-based robust mixed-integer linear programming to optimally support the system make the contribution of the paper novel and unique. The main objective is to schedule manufacturing (non-shiftable) and non-manufacturing (shiftable and interruptible) loads, and distributed energy resources based on the real-time-pricing policy in an interactive decentralized operation of a capacitated multi-carrier energy production-consumption system. Compared to the conventional system, the results outline 64.63%, 1.62%, 100%, and 65.23% less Carbon dioxide emissions, net production, power exchange, and total costs, on average. The proposed framework is preferable to the framework that is based on the use of combined heat and power systems, at least in terms of a reduction in production costs. Considering both the supply- and demand-side uncertainties, the framework performs good trade-offs between solution robustness and model robustness, and environmental and economic concerns. •Introducing the idea of Smart Energy-Aware Manufacturing Plant Scheduling.•Proposing a new multi-objective risk-based robust Mixed Integer Linear Programming.•Obtaining 64.63%, 1.62%, and 65.23% less emission, production, and total costs.•Providing a good trade-off between solution and model robustness.•Providing a constructive trade-off between environmental and economic concerns. |
| ArticleNumber | 118385 |
| Author | Golpîra, Hêriş |
| Author_xml | – sequence: 1 givenname: Hêriş surname: Golpîra fullname: Golpîra, Hêriş email: herishgolpira@gmail.com, H_Golpira@iausdj.ac.ir organization: Department of Industrial Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran |
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| Keywords | Conditional Value-at-Risk Combined cooling, Heat and power (CCHP) system Energy efficiency Robust optimization |
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| SubjectTerms | Carbon dioxide Carbon dioxide emissions Cogeneration Combined cooling, Heat and power (CCHP) system Conditional Value-at-Risk cooling Distributed generation Economic models Economics energy Energy efficiency Energy management Energy policy Energy resources Energy sources heat Heat exchange Industrial energy Industrial plants Integer programming issues and policy Linear programming Manufacturing Manufacturing industry Mixed integer Multiple objective analysis Optimization Production costs Renewable energy Risk levels Robust optimization Robustness (mathematics) Schedules Scheduling Stress concentration Uncertainty |
| Title | Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach |
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