Publication detail

Waste-to-energy plant operation planning based on stochastic simulation

TOUŠ, M. PAVLAS, M. STEHLÍK, P.

Original Title

Waste-to-energy plant operation planning based on stochastic simulation

English Title

Waste-to-energy plant operation planning based on stochastic simulation

Type

conference paper

Language

en

Original Abstract

In many cases, waste-to-energy (WtE) plants are combined heat and power producers. They are often integrated into a central heating system and they also export electricity to a grid. Therefore, they have to plan their operation for the next day, next month, etc. However, it may be a challenging task due to stochastic nature of some input variables such as varying lower heating value of waste, boiler performance resulting in fluctuating steam parameters, irregular internal steam consumption or its export. This paper presents a novel tool for a WtE plant operation planning under uncertainty. The crucial part of the tool is a stochastic model of a technology. The stochastic model was developed using operational data from an existing plant. The model was then implemented into simulation tool and well-known Monte Carlo simulation method was applied. Utilization of simulation results for operation planning is described on an example and the contribution of stochastic approach is evaluated using historical data.

English abstract

In many cases, waste-to-energy (WtE) plants are combined heat and power producers. They are often integrated into a central heating system and they also export electricity to a grid. Therefore, they have to plan their operation for the next day, next month, etc. However, it may be a challenging task due to stochastic nature of some input variables such as varying lower heating value of waste, boiler performance resulting in fluctuating steam parameters, irregular internal steam consumption or its export. This paper presents a novel tool for a WtE plant operation planning under uncertainty. The crucial part of the tool is a stochastic model of a technology. The stochastic model was developed using operational data from an existing plant. The model was then implemented into simulation tool and well-known Monte Carlo simulation method was applied. Utilization of simulation results for operation planning is described on an example and the contribution of stochastic approach is evaluated using historical data.

Keywords

waste-to-energy, operation planning, stochastic simulation

RIV year

2014

Released

23.08.2014

ISBN

978-88-95608-30-3

Book

Proceedings of the 17th CONFERENCE ON PROCESS INTEGRATION, MODELLING AND OPTIMISATION FOR ENERGY SAVING AND POLLUTION REDUCTION PRES 2014

Pages from

673

Pages to

678

Pages count

6

Documents

BibTex


@inproceedings{BUT109197,
  author="Michal {Touš} and Martin {Pavlas} and Petr {Stehlík}",
  title="Waste-to-energy plant operation planning based on stochastic simulation",
  annote="In many cases, waste-to-energy (WtE) plants are combined heat and power producers. They are often integrated into a central heating system and they also export electricity to a grid. Therefore, they have to plan their operation for the next day, next month, etc. However, it may be a challenging task due to stochastic nature of some input variables such as varying lower heating value of waste, boiler performance resulting in fluctuating steam parameters, irregular internal steam consumption or its export. This paper presents a novel tool for a WtE plant operation planning under uncertainty. The crucial part of the tool is a stochastic model of a technology. The stochastic model was developed using operational data from an existing plant. The model was then implemented into simulation tool and well-known Monte Carlo simulation method was applied. Utilization of simulation results for operation planning is described on an example and the contribution of stochastic approach is evaluated using historical data.",
  booktitle="Proceedings of the 17th CONFERENCE ON PROCESS INTEGRATION, MODELLING AND OPTIMISATION FOR ENERGY SAVING AND POLLUTION REDUCTION PRES 2014",
  chapter="109197",
  doi="10.3303/CET1439113",
  howpublished="print",
  year="2014",
  month="august",
  pages="673--678",
  type="conference paper"
}