Certainty through uncertainty: Stochastic optimization of grid-integrated large-scale energy storage in Germany

Leonardo K.K. Maia*, Anton Ochoa Bique, Edwin Zondervan

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

This work presents an approach to optimize the scheduling and determine the requirements for power systems in the future electricity grid, taking into account the goals of the energy transition in Germany and neighboring countries under uncertain conditions. The value of stochastic solution (VSS) is used as a performance index to compare the deterministic and stochastic approaches. A VSS of up to €800 million of annual grid gross profit is calculated, clearly demonstrating the benefits a stochastic approach brings when determining the required infrastructure investments for the future electricity grid. Energy storage requirements are estimated while considering grid. For high load loss penalties, additional storage capacities of up to 42 GWh are calculated. The uncertainty in the electricity demand has the most expressive impact on grid operation costs, and is for this reason used to generate the scenario array for the stochastic simulations.

Original languageEnglish
JournalPhysical Sciences Reviews
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • energy storage
  • energy systems
  • energy transition
  • mathematical programming
  • stochastic optimization

Fingerprint Dive into the research topics of 'Certainty through uncertainty: Stochastic optimization of grid-integrated large-scale energy storage in Germany'. Together they form a unique fingerprint.

Cite this