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 proceedingConference article in proceedingsScientificpeer-review


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 languageEnglish
Title of host publication33rd European Symposium on Computer Aided Process Engineering
EditorsAntonios C. Kokossis, Michael C. Georgiadis, Efstratios Pistikopoulos
Number of pages6
ISBN (Print)978-0-443-15274-0
Publication statusPublished - 18 Jun 2023
MoE publication typeA4 Conference publication
EventEuropean Symposium on Computer Aided Process Engineering - Athens, Greece
Duration: 18 Jun 202321 Jun 2023
Conference number: 33

Publication series

NameComputer Aided Chemical Engineering
ISSN (Print)1570-7946
ISSN (Electronic)2543-1331


ConferenceEuropean Symposium on Computer Aided Process Engineering
Abbreviated titleESCAPE


  • stochastic programming
  • energy storage
  • solar energy
  • electricity market


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