End-effect mitigation in multi-period stochastic programming of energy storage operations

Teemu Ikonen; Dongho Han; Jay H. Lee; Iiro Harjunkoski

doi:10.1016/B978-0-443-15274-0.50479-0

End-effect mitigation in multi-period stochastic programming of energy storage operations

Teemu Ikonen^*, Dongho Han, Jay H. Lee, Iiro Harjunkoski

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

Energy storage units offer vital balancing power for energy systems with increasing amount of variable renewable energy sources. The operation of such systems can be optimized by stochastic programming, which anticipates the uncertainty related to the variable energy generation. However, these optimization problems can only be formulated for optimization horizons of a limited length (e.g., 24 or 48 h), due to the rapidly increasing problem size. In this work, we propose the resulting end-effect to be mitigated by valuation of the terminal stored energy level based on an electricity price forecast. We present results on a hybrid energy system, consisting of photovoltaic power generation and an energy storage unit, which trades electricity in the day-ahead market.

Original language	English
Title of host publication	33rd European Symposium on Computer Aided Process Engineering
Editors	Antonios C. Kokossis, Michael C. Georgiadis, Efstratios Pistikopoulos
Publisher	Elsevier
Pages	3007-3012
Number of pages	6
ISBN (Print)	978-0-443-15274-0
DOIs	https://doi.org/10.1016/B978-0-443-15274-0.50479-0
Publication status	Published - 18 Jun 2023
MoE publication type	A4 Conference publication
Event	European Symposium on Computer Aided Process Engineering - Athens, Greece Duration: 18 Jun 2023 → 21 Jun 2023 Conference number: 33

Publication series

Name	Computer Aided Chemical Engineering
Publisher	Elsevier
Volume	52
ISSN (Print)	1570-7946
ISSN (Electronic)	2543-1331

Conference

Conference	European Symposium on Computer Aided Process Engineering
Abbreviated title	ESCAPE
Country/Territory	Greece
City	Athens
Period	18/06/2023 → 21/06/2023

Keywords

stochastic programming
energy storage
solar energy
electricity market

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/B978-0-443-15274-0.50479-0

Cite this

Ikonen, T., Han, D., Lee, J. H., & Harjunkoski, I. (2023). End-effect mitigation in multi-period stochastic programming of energy storage operations. In A. C. Kokossis, M. C. Georgiadis, & E. Pistikopoulos (Eds.), 33rd European Symposium on Computer Aided Process Engineering (pp. 3007-3012). (Computer Aided Chemical Engineering; Vol. 52). Elsevier. https://doi.org/10.1016/B978-0-443-15274-0.50479-0

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title = "End-effect mitigation in multi-period stochastic programming of energy storage operations",

abstract = "Energy storage units offer vital balancing power for energy systems with increasing amount of variable renewable energy sources. The operation of such systems can be optimized by stochastic programming, which anticipates the uncertainty related to the variable energy generation. However, these optimization problems can only be formulated for optimization horizons of a limited length (e.g., 24 or 48 h), due to the rapidly increasing problem size. In this work, we propose the resulting end-effect to be mitigated by valuation of the terminal stored energy level based on an electricity price forecast. We present results on a hybrid energy system, consisting of photovoltaic power generation and an energy storage unit, which trades electricity in the day-ahead market.",

keywords = "stochastic programming, energy storage, solar energy, electricity market",

author = "Teemu Ikonen and Dongho Han and Lee, {Jay H.} and Iiro Harjunkoski",

year = "2023",

month = jun,

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doi = "10.1016/B978-0-443-15274-0.50479-0",

language = "English",

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series = "Computer Aided Chemical Engineering",

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editor = "Kokossis, {Antonios C.} and Georgiadis, {Michael C.} and Efstratios Pistikopoulos",

booktitle = "33rd European Symposium on Computer Aided Process Engineering",

address = "Netherlands",

note = "European Symposium on Computer Aided Process Engineering, ESCAPE ; Conference date: 18-06-2023 Through 21-06-2023",

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Ikonen, T, Han, D, Lee, JH & Harjunkoski, I 2023, End-effect mitigation in multi-period stochastic programming of energy storage operations. in AC Kokossis, MC Georgiadis & E Pistikopoulos (eds), 33rd European Symposium on Computer Aided Process Engineering. Computer Aided Chemical Engineering, vol. 52, Elsevier, pp. 3007-3012, European Symposium on Computer Aided Process Engineering, Athens, Greece, 18/06/2023. https://doi.org/10.1016/B978-0-443-15274-0.50479-0

End-effect mitigation in multi-period stochastic programming of energy storage operations. / Ikonen, Teemu; Han, Dongho; Lee, Jay H. et al.
33rd European Symposium on Computer Aided Process Engineering. ed. / Antonios C. Kokossis; Michael C. Georgiadis; Efstratios Pistikopoulos. Elsevier, 2023. p. 3007-3012 (Computer Aided Chemical Engineering; Vol. 52).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - End-effect mitigation in multi-period stochastic programming of energy storage operations

AU - Ikonen, Teemu

AU - Han, Dongho

AU - Lee, Jay H.

AU - Harjunkoski, Iiro

N1 - Conference code: 33

PY - 2023/6/18

Y1 - 2023/6/18

N2 - Energy storage units offer vital balancing power for energy systems with increasing amount of variable renewable energy sources. The operation of such systems can be optimized by stochastic programming, which anticipates the uncertainty related to the variable energy generation. However, these optimization problems can only be formulated for optimization horizons of a limited length (e.g., 24 or 48 h), due to the rapidly increasing problem size. In this work, we propose the resulting end-effect to be mitigated by valuation of the terminal stored energy level based on an electricity price forecast. We present results on a hybrid energy system, consisting of photovoltaic power generation and an energy storage unit, which trades electricity in the day-ahead market.

AB - Energy storage units offer vital balancing power for energy systems with increasing amount of variable renewable energy sources. The operation of such systems can be optimized by stochastic programming, which anticipates the uncertainty related to the variable energy generation. However, these optimization problems can only be formulated for optimization horizons of a limited length (e.g., 24 or 48 h), due to the rapidly increasing problem size. In this work, we propose the resulting end-effect to be mitigated by valuation of the terminal stored energy level based on an electricity price forecast. We present results on a hybrid energy system, consisting of photovoltaic power generation and an energy storage unit, which trades electricity in the day-ahead market.

KW - stochastic programming

KW - energy storage

KW - solar energy

KW - electricity market

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U2 - 10.1016/B978-0-443-15274-0.50479-0

DO - 10.1016/B978-0-443-15274-0.50479-0

M3 - Conference article in proceedings

SN - 978-0-443-15274-0

T3 - Computer Aided Chemical Engineering

SP - 3007

EP - 3012

BT - 33rd European Symposium on Computer Aided Process Engineering

A2 - Kokossis, Antonios C.

A2 - Georgiadis, Michael C.

A2 - Pistikopoulos, Efstratios

PB - Elsevier

T2 - European Symposium on Computer Aided Process Engineering

Y2 - 18 June 2023 through 21 June 2023

ER -

End-effect mitigation in multi-period stochastic programming of energy storage operations

Abstract

Publication series

Conference

Keywords

UN SDGs

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