Improving an Integer Linear Programming Model of an Ecovat Buffer by Adding Long-Term Planning

Gijs J.H. de Goeijen, Gerard J.M. Smit, Johann L. Hurink

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
51 Downloads (Pure)

Abstract

The Ecovat is a seasonal thermal storage solution consisting of a large underground water tank divided into a number of virtual segments that can be individually charged and discharged. The goal of the Ecovat is to supply heat demand to a neighborhood throughout the entire year. In this work, we extend an integer linear programming model to describe the charging and discharging of such an Ecovat buffer by adding a long-term (yearly) planning step to the model. We compare the results from the model using this extension to previously obtained results and show significant improvements when looking at the combination of costs and the energy content of the buffer at the end of the optimization. Furthermore, we show that the model is very robust against prediction errors. For this, we compare two different cases: one case in which we assume perfect predictions are available and one case in which we assume no predictions are available. The largest observed difference in costs between these two cases is less than 2%.
Original languageEnglish
Article number2039
Number of pages18
JournalEnergies
DOIs
Publication statusPublished - 3 Dec 2017

Fingerprint

Integer Linear Programming
Linear programming
Programming Model
Buffer
Linear Model
Planning
Prediction
Costs
Prediction Error
Water tanks
Heat
Entire
Model
Water
Groundwater
Optimization
Energy
Hot Temperature

Keywords

  • Smart Grids
  • seasonal thermal storage
  • modeling
  • Integer linear programming

Cite this

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abstract = "The Ecovat is a seasonal thermal storage solution consisting of a large underground water tank divided into a number of virtual segments that can be individually charged and discharged. The goal of the Ecovat is to supply heat demand to a neighborhood throughout the entire year. In this work, we extend an integer linear programming model to describe the charging and discharging of such an Ecovat buffer by adding a long-term (yearly) planning step to the model. We compare the results from the model using this extension to previously obtained results and show significant improvements when looking at the combination of costs and the energy content of the buffer at the end of the optimization. Furthermore, we show that the model is very robust against prediction errors. For this, we compare two different cases: one case in which we assume perfect predictions are available and one case in which we assume no predictions are available. The largest observed difference in costs between these two cases is less than 2{\%}.",
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Improving an Integer Linear Programming Model of an Ecovat Buffer by Adding Long-Term Planning. / de Goeijen, Gijs J.H.; Smit, Gerard J.M.; Hurink, Johann L.

In: Energies, 03.12.2017.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Improving an Integer Linear Programming Model of an Ecovat Buffer by Adding Long-Term Planning

AU - de Goeijen, Gijs J.H.

AU - Smit, Gerard J.M.

AU - Hurink, Johann L.

PY - 2017/12/3

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N2 - The Ecovat is a seasonal thermal storage solution consisting of a large underground water tank divided into a number of virtual segments that can be individually charged and discharged. The goal of the Ecovat is to supply heat demand to a neighborhood throughout the entire year. In this work, we extend an integer linear programming model to describe the charging and discharging of such an Ecovat buffer by adding a long-term (yearly) planning step to the model. We compare the results from the model using this extension to previously obtained results and show significant improvements when looking at the combination of costs and the energy content of the buffer at the end of the optimization. Furthermore, we show that the model is very robust against prediction errors. For this, we compare two different cases: one case in which we assume perfect predictions are available and one case in which we assume no predictions are available. The largest observed difference in costs between these two cases is less than 2%.

AB - The Ecovat is a seasonal thermal storage solution consisting of a large underground water tank divided into a number of virtual segments that can be individually charged and discharged. The goal of the Ecovat is to supply heat demand to a neighborhood throughout the entire year. In this work, we extend an integer linear programming model to describe the charging and discharging of such an Ecovat buffer by adding a long-term (yearly) planning step to the model. We compare the results from the model using this extension to previously obtained results and show significant improvements when looking at the combination of costs and the energy content of the buffer at the end of the optimization. Furthermore, we show that the model is very robust against prediction errors. For this, we compare two different cases: one case in which we assume perfect predictions are available and one case in which we assume no predictions are available. The largest observed difference in costs between these two cases is less than 2%.

KW - Smart Grids

KW - seasonal thermal storage

KW - modeling

KW - Integer linear programming

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