A General Representation for the Modeling of Energy Supply Chains

Kalaitzidou, Magdalini A.; Georgiadis, Michael C.; Kopanos, Georgios M.

doi:10.1016/b978-0-444-63428-3.50135-1

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…Their work accounted for both centralized and distributed process networks, which is another key decision. Some models proposed in the literature attempt to cover optimizing for more general supply chains [15]. A review of further case studies for biomass-based energy supply design was provided by [16].…”

Section: Biomass-based Energy Supplymentioning

confidence: 99%

Modeling of a Biomass-Based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Éles,

Heckl,

Cabezas

2024

Energies

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In this work, a modeling technique utilizing the P-Graph framework was used for a case study involving biomass-based local energy production. In recent years, distributed energy systems gained attention. These systems aim to satisfy energy supply demands, support the local economy, decrease transportation needs and dependence on imports, and, in general, obtain a more sustainable energy production process. Designing such systems is a challenge, for which novel optimization approaches were developed to help decision making. Previous work used the P-Graph framework to optimize energy production in a small rural area, involving manure, intercrops, grass, and corn silage as inputs and fermenters. Biogas is produced in fermenters, and Combined Heat and Power (CHP) plants provide heat and electricity. A more recent result introduced the concept of operations with flexible inputs in the P-Graph framework. In this work, the concept of flexible inputs was applied to model fermenters in the original case study. A new implementation of the original decision problem was made both as a Mixed-Integer Linear Programming (MILP) model and as a purely P-Graph model by using the flexible input technique. Both approaches provided the same optimal solution, with a 31% larger profit than the fixed input model.

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Section: Biomass-based Energy Supplymentioning

confidence: 99%

Modeling of a Biomass-Based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Éles,

Heckl,

Cabezas

2024

Energies

View full text Add to dashboard Cite

show abstract

“…Their work accounted for both centralized and distributed process networks, which is another key decision. Some models proposed in the literature attempt to cover optimizing for more general supply chains [7]. A review of further case studies for biomass-based energy supply design was provided by [8].…”

Section: Biomass-based Energy Supplymentioning

confidence: 99%

Modeling of a Biomass-based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Éles,

Heckl,

Cabezas

2023

Preprint

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In this work, a modeling technique utilizing the P-Graph framework was used for a case 1 study involving biomass-based local energy production. In recent years, distributed energy systems 2 gained attention. These systems aim at satisfying energy supply demands, supporting the local 3 economy, decreasing transportation needs and dependence on imports, and in general obtaining a 4 more sustainable energy production process. Designing such systems is a challenge, for which novel 5 optimization approaches were developed to help decision-making. Previous work used the P-Graph 6 framework to optimize energy production in a small rural area, involving manure, intercrops, grass, 7 and corn silage as inputs, and fermenters. Biogas is produced in fermenters, and Combined Heat 8 and Power (CHP) plants provide heat and electricity. A more recent result introduced the concept of 9 operations with flexible inputs in the P-Graph framework. In this work, the concept of flexible inputs 10 was applied to model fermenters in the original case study. A new implementation of the original 11 decision problem was made both as a Mixed-Integer Linear Programming (MILP) model and as a 12 purely P-Graph model by using the flexible input technique. Both approaches provided the same 13 optimal solution, with a 31% larger profit than originally reported.

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“…The complexity of the systems to be designed optimally yields for adequate modeling and optimization tools, regardless of the scope being a single plant or a whole region. Novel, general methods are published [8], using mathematical programming solutions which are a conventional way of modeling. But due to their limitation in solving larger or too special problems, specific case studies may require other model developing techniques.…”

mentioning

confidence: 99%

Evaluation of the Energy Supply Options of a Manufacturing Plant by the Application of the P-Graph Framework

et al. 2019

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Industrial applications nowadays are facing the complexity of the problem of finding an optimal energy supply composition. Heating and electricity needs vary throughout a year and need to be addressed. There is usually power available from the market, but a company has other investment options to consider, such as solar power, or utilization of local biomass. Fixed and proportional investment and operational costs must be compared to long-term cost-efficiency. The P-Graph framework is an effective tool in the design and synthesis of process networks, and is capable of showing optimal decisions. In the present work, a new P-Graph model was implemented to address the synthesis of the energy supply options of a manufacturing plant in Hungary. Compared to the original approach, a multi-periodic scheme was applied for heating and electricity demands. Also, the pelletizer and biogas plant investments are modeled in the P-Graph with a new technique that better reflects equipment capacities and flexible input ratios. The best solutions in this case study in terms of total costs are listed. It can be concluded that a long-term investment horizon is needed for the incorporation of sustainable energy sources into the system to be cost-efficient.

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A General Representation for the Modeling of Energy Supply Chains

Cited by 5 publications

References 4 publications

Modeling of a Biomass-Based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Modeling of a Biomass-Based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Modeling of a Biomass-based Energy Production Case Study Using Flexible Inputs with the P-Graph Framework

Evaluation of the Energy Supply Options of a Manufacturing Plant by the Application of the P-Graph Framework

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