Publication result detail

Waste bunker size optimization under uncertainty: Application of inventory models with real data simulation

ZDRAŽIL, J.; MAŤCHA, M.; HRABEC, D.; ŠOMPLÁK, R.; KRŇÁVEK, J.; JADRNÝ, J.

Original Title

Waste bunker size optimization under uncertainty: Application of inventory models with real data simulation

English Title

Waste bunker size optimization under uncertainty: Application of inventory models with real data simulation

Type

WoS Article

Original Abstract

Waste-to-Energy (WtE) technologies play a prominent role in recovering energy from waste. One of the aspects ensuring the operability and economic sustainability of WtE plants is the size optimization of a waste bunker assigned to each WtE plant, whose main target is to ensure waste homogeneity for effective operation. Each WtE plant faces various uncertain challenges, such as planned and unplanned shutdowns during which the plant is inactive and not ideally coordinated with waste collection companies, further importing the collected waste into the waste bunker, mainly due to existing contracts. This work aims to develop a scenario-based model to support strategic capacity planning by capturing various uncertain attributes and optimizing the waste bunker size while minimizing the total costs composing the investment, inventory, and waste shortage costs. The model is tested on a case study from the Czech Republic. The main result can be summarized such that for a specific case of a newly situated WtE facility with a considered capacity of 100kt/y, the model suggests a bunker of size ca. 4,200m3 for a middle scenario. However, this is strongly related to other attributes of a particular WtE project (e.g., waste properties or cost parameters).

English abstract

Waste-to-Energy (WtE) technologies play a prominent role in recovering energy from waste. One of the aspects ensuring the operability and economic sustainability of WtE plants is the size optimization of a waste bunker assigned to each WtE plant, whose main target is to ensure waste homogeneity for effective operation. Each WtE plant faces various uncertain challenges, such as planned and unplanned shutdowns during which the plant is inactive and not ideally coordinated with waste collection companies, further importing the collected waste into the waste bunker, mainly due to existing contracts. This work aims to develop a scenario-based model to support strategic capacity planning by capturing various uncertain attributes and optimizing the waste bunker size while minimizing the total costs composing the investment, inventory, and waste shortage costs. The model is tested on a case study from the Czech Republic. The main result can be summarized such that for a specific case of a newly situated WtE facility with a considered capacity of 100kt/y, the model suggests a bunker of size ca. 4,200m3 for a middle scenario. However, this is strongly related to other attributes of a particular WtE project (e.g., waste properties or cost parameters).

Keywords

Breakdown and maintenance; Monte Carlo simulation; Shutdown uncertainty; Size allocation; Waste-to-energy

Key words in English

Breakdown and maintenance; Monte Carlo simulation; Shutdown uncertainty; Size allocation; Waste-to-energy

Authors

ZDRAŽIL, J.; MAŤCHA, M.; HRABEC, D.; ŠOMPLÁK, R.; KRŇÁVEK, J.; JADRNÝ, J.

RIV year

2024

Released

01.12.2023

ISBN

2213-1396

Periodical

Sustainable Energy Technologies and Assessments

Volume

60

Number

1

State

Kingdom of the Netherlands

Pages from

1

Pages to

11

Pages count

11

URL

BibTex

@article{BUT185068,
  author="Jan {Zdražil} and Marek {Maťcha} and Dušan {Hrabec} and Radovan {Šomplák} and Jan {Krňávek} and Josef {Jadrný}",
  title="Waste bunker size optimization under uncertainty: Application of inventory models with real data simulation",
  journal="Sustainable Energy Technologies and Assessments",
  year="2023",
  volume="60",
  number="1",
  pages="1--11",
  doi="10.1016/j.seta.2023.103478",
  issn="2213-1388",
  url="https://www.sciencedirect.com/science/article/pii/S221313882300471X"
}